Date : 2024-06-18 => 2024-06-20
Lieu : Rennes, France

Save the date! The ACM Conference on Reproducibility and Replicability will take place on:

June 18-20, 2024 at INRIA, Rennes, France
This will be a hybrid event – remote participation is welcome.
https://acm-rep.github.io/2024

About ACM REP
The 2024 ACM Conference on Reproducibility and Replicability (ACM REP ‘24) aims to bring together experts and practitioners engaged in the advancement and conduct of reproducible science in computing disciplines.

What’s next?
The call for paper will open soon, the deadline for paper submission will be: January 29, 2024.

For more info: https://acm-rep.github.io/2024

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Annonce en lien avec l’Action/le Réseau :

Thème :

Exploitation de données massives

Présentation :

L’école thématique CNRS MDD « Masses de données distribuées » est une école thématique récurrente ayant lieu tous les deux ans depuis 2010. Cette école est une émanation de la communauté des bases de données en France, structurée autour de la conférence BDA : Gestion de données – principes et applications, qui a fêté ses 30 ans d’existence en 2016. Si notre conférence est le lieu de rencontre de notre communauté, l’école thématique MDD permet d’exposer en détails des thèmes fondamentaux pour la compréhension de l’évolution de notre domaine de recherche, et de préparer les doctorant(e)s à suivre – et provoquer – ses évolutions.

Du : 2024-06-23

Au : 2024-06-28

Lieu : Ceillac

Site Web : https://cedric.cnam.fr/lab/confs/mdd2024/

Date : 2024-06-23 => 2024-06-27
Lieu : Ceillac-en-Queyras

The thematic school ‘Masses de Données’ (MDD) originates from the research community in databases. Its aim is to strengthen the educational component (tutorials) within an independent event, leading to the creation of the MDD summer-school.
Our thematic school aims to shed light on various societal issues by inviting experts from various computer science and legal disciplines. The general theme, “Responsible data management,” will be divided into the following 5 axe.

Please join us with the provided link.

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Date : 2024-06-24 => 2024-07-01
Lieu : INSA de Rouen (76)

Les graphes sont au cœur de nombreuses thématiques de recherche ou apparaissent spontanément dans des projets où on ne les attendaient pas. Le traitement de ces objets peut mobiliser plusieurs domaines de recherche tels que la théorie des graphes, la modélisation de données sémantiques ou dynamiques, le traitement de données définies sur des graphes ou l’apprentissage de données définies sur ou par des graphes. Cette apparente disparité d’approches cache toutefois une utilisation de nombreux outils communs (e.g. plus grand sous graphe commun, pattern de graphes, métrique sur graphe…). L’objectif de la formation est de fournir une vue d’ensemble des approches détaillées ci-dessous pour fournir une vue d’ensemble du traitement de données sur graphes et permettre des échanges fructueux entre communautés scientifiques.

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Date : 2024-06-25 => 2024-06-28
Lieu : Lyon, France

————————–
DEBS 2024 Joint Conference
25th – 28th June, 2024
Lyon, France
https://2024.debs.org
————————–

DEBS 2024 Call for Participation

The ACM International Conference on Distributed and Event-Based Systems (DEBS) is a premier venue for academia and industry to discuss cutting-edge research of distributed and event-based computing and data processing. DEBS 2024 will be a forum dedicated to the dissemination of original research, the discussion of practical insights, and the reporting of experiences relevant to distributed and event-based systems.

The DEBS conference covers topics in distributed and event-based computing for a wide range of application domains and computing environments. The conference aims to present novel solutions for collecting, detecting, processing, analyzing, and responding to events through distributed middleware, systems, and platforms.

Topics covered by the conference include, but are not limited to
* models, architectures, and paradigms
* systems and software
* applications and use-cases
of distributed and event-based computing and data analysis.

The conference is held in Lyon, the culinary heart of France. The city enchants with its rich history and stunning beauty. Its UNESCO-listed Old Town, Vieux Lyon, features cobblestone streets and Renaissance architecture. The Basilica of Notre-Dame de Fourvière offers breathtaking city views, while the expansive Parc de la Tête d’Or provides a serene retreat with gardens and a lake. Lyon’s charm lies in its blend of culture, gourmet cuisine, and picturesque scenery.

Registration

The registration website is available at https://www.ecolloque.com/debs-2024/en/new/
More details on registration prices and cancellation can be found in on the website page (https://2024.debs.org/registration/).

Conference: June 25-28th, 2024

**Organisers**

General chairs
* Angela Bonifati
* Riccardo Tommasini
PC chairs
* Avrilia Floratou, Microsoft
* Tilmann Rabl, HPI

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Date : 2024-07-01 => 2024-07-05
Lieu : Campus SophiaTech (Polytech Sophia Antipolis) du 1er au 5 juillet 2024

La Deep Learning School est de retour après 2 années de pause.

Comme lors des précédentes éditions, la Deep Learning School se déroulera pendant 5 jours sur le Campus SophiaTech (Polytech Sophia Antipolis) du 1er au 5 juillet 2024.

Chaque jour, une demi-journée sera consacrée à un cours par une chercheuse ou un chercheur mondialement reconnu⸱e dans le domaine du Deep Learning, et l’autre demi-journée à un Lab de 3 heures au cours duquel les notions abordées en cours seront appliquées directement.

Pendant ces cinq jours, les participant⸱e⸱s auront l’opportunité d’être formé⸱e⸱s par des experts de renommée mondiale :
– Lundi 1er juillet : IA interprétable par la Pr Cynthia Rudin, Duke University (USA)
– Mardi 2 juillet : NLP & Frugal AI par la Pr Emma Strubell, Carnegie Mellon University (USA)
– Mercredi 3 juillet : IA responsable et équité par la Pr Golnoosh Farnadi, Université McGill et Mila (Canada)
– Jeudi 4 juillet : IA et physique/simulation numérique par le Pr Amir Barati Farimani, Université Carnegie Mellon (États-Unis)
– Vendredi 5 juillet : Modèles fondation – Des images au langage et vice versa, par le Pr Matthieu Cord, Sorbonne Université, directeur scientifique de Valeo AI.

Vous trouverez toutes les informations relatives à ces spécialistes et à leurs interventions sur notre site web : https://3ia.univ-cotedazur.eu/deep-learning-school/homepage

Vous pourrez vous inscrire ici : https://3ia.univ-cotedazur.eu/deep-learning-school/registration

Nous vous attendons nombreuses et nombreux.
L’équipe de la Deep Learning School @UniCA

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Annonce en lien avec l’Action/le Réseau :

Thème :

IA ; Imagerie Médicale

Présentation :

Cette école d’été s’adresse aux chercheurs débutants ou plus expérimentés en imagerie médicale, souhaitant approfondir leurs connaissances en apprentissage automatique et son application à de multiples problèmes dans ce domaine. Le programme inclut diverses présentations d’experts (15h au total) couvrant les bases de l’apprentissage automatique, les réseaux de neurones en apprentissage profond, de même que des sujets plus avancés tels que les modèles génératifs, l’adaptation de domaine, l’apprentissage faiblement supervisé et les modèles fondateurs. Les participants pourront également mettre en pratiques les concepts présentés à l’école grâce à 4 séances hands-on de 3h chacune.

Du : 2024-07-08

Au : 2024-07-12

Lieu : École de technologie supérieure (ÉTS) de Montréal, Canada

Site Web : https://event.fourwaves.com/dlmi2024

Date : 2024-07-08 => 2024-07-11
Lieu : HEC Paris, Jouy-en-Josas

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Date : 2024-07-22 => 2024-07-26
Lieu : Saint-Étienne

*Call for Participation 2024 Summer School on AI Technologies for Trust, Interoperability, Autonomy and Resilience in Industry 4.0*

We invite PhD students, academics, and researcher staff from academia and industry to apply to the Summer School on AI Technologies for Trust, Interoperability, Autonomy and Resilience in Industry 4.0 (henceforth AI4Industry).

The summer school aims to teach the state of the art of the use of AI technologies and models to tackle the challenges of data revolution and to increase automation of cognitive tasks to develop a trustful and resilient Industry 4.0 (or Industry of the Future). The summer school is organized around concrete industry problems structured as use cases. These use cases aim to stimulate the discussion at the academic institutions toward addressing real-world problems and to showcase innovative solutions to industrial partners.

During the summer school, participants attend lectures of AI technologies and carry out practical exercises dedicated to applying these technologies to solve concrete industry problems. The summer school addresses various aspects of AI in Industry with a particular emphasis on:

* Web of Things
* Knowledge Graphs
* Multi-Agent Systems
* Trustworthy and Responsible AI

Half of the summer school is dedicated to practical work (through a hackathon) while the other half is meant to introduce the theoretical foundations underlying the hackathon’s framework.

The AI4Industry Summer School series website provides more information about the summer school.

*Important Dates*

* *Application on a rolling basis*: until June 15, 2024
* *Notification*: 2 weeks after application submission
* *Summer School*: July 22-26, 2024

*Contact *

contact-ai4industry@listes.emse.fr

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Date : 2024-07-30 => 2024-08-02
Lieu : Vienne Autriche

The 5th International Workshop on Graph-based Approaches for CyberSecurity to be held in conjunction with the 19th International Conference on Availability, Reliability and Security
Vienna, Austria
July 30 – August 02, 2024

Topics of interest include, but are not limited to

Knowledge graphs and ontologies of cyberspaces and digital twins
Attack graphs modeling and application, graph-based threat assessment
Graph-based models for network modeling and cyber situational awareness
Graph-based approaches to network traffic analysis and forensics
Intrusion, anomaly, and botnet activity detection using graph data
Graph-based anomaly detection for network security and management
Graph application in access controls, security policies
Graph-based malware detection
Autoencoders and representation learning for graphs and knowledge graphs
Graph embedding techniques for network security and management problems
Graph databases and graph-based tools for security data analysis
Visualization and analysis of dynamic large-scale graphs and graph streams
Novel applications of static/dynamic and large graphs in network security and management

IMPORTANT DATES
Submission Deadline: April 29, 2024
Author Notification: May 29, 2024
Proceedings Version: June 18, 2024
Workshop days: July 30 – August 02, 2024

The submission guidelines valid for the workshop are the same as for the ARES conference. They can be found at https://www.ares-conference.eu/conference/submission/.

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Date : 2024-08-05
Lieu : Co-localisé avec la conférence IJCAI 2024, île de Jeju, Corée du Sud

Call For Papers

The 3^rd International Workshop on Spatio-Temporal Reasoning and Learning (STRL 2024) will take place in Jeju, South Korea, collocated with IJCAI 2024.

Website: https://www.lirmm.fr/strl2024/

Introduction

Opposing the false dilemma of logical reasoning vs machine learning, we argue for a synergy between these two paradigms in order to obtain hybrid AI systems that will be robust, generalizable, and transferable.

Indeed, it is well-known that machine learning only includes statistical information and, therefore, is not inherently able to capture perturbations (interventions or changes in the environment), or perform reasoning and planning. Ideally, (the training of) machine learning models should be tied to assumptions that align with physics and human cognition to allow for these models to be re-used and re-purposed in novel scenarios.

On the other hand, it is also the case that logic in itself can be brittle too, and logic further assumes that the symbols with which it can reason are already given.

It is becoming ever more evident in the literature that modular AI architectures should be prioritized, where the involved knowledge about the world and the reality that we are operating in is decomposed into independent and recomposable pieces, as such an approach should only increase the chances that these systems behave in a causally sound manner.

You may find details about previous editions of this workshop via the links below:

• STRL 2023
• STRL 2022

The aim of this workshop is to formalize such a synergy between logical reasoning and machine learning that will be grounded on spatial and temporal knowledge.

We argue that the calculi associated with the spatial and temporal reasoning community, be it qualitative or quantitative, naturally build upon physics and human cognition, and could therefore form a module that would be beneficial towards causal representation learning. A (symbolic) spatio-temporal knowledge base could provide a dependable causal seed upon which machine learning models could generalize, and exploring this direction from various perspectives is the main theme here.

Topics

In this workshop, we invite the research community in artificial intelligence to submit works related to the proposed integration of spatial and temporal reasoning with machine learning, revolving around the following topic areas:

• Real-world problems / applications involving spatio-temporal data
• Spatial, temporal, and spatio-temporal knowledge graphs
• Spatio-temporal data mining / analysis
• Space and time in narratives
• Declarative spatial reasoning
• Spatial and temporal language understanding with and without additional modalities (e.g., vision)
• Neuro-symbolic approaches for spatio-temporal reasoning and learning
• Probabilistic world models for spatio-temporal reasoning and learning
• Probabilistic inference for spatio-temporal reasoning and learning
• Datasets for spatio-temporal reasoning and learning
• Metrics for assessing spatio-temporal reasoning and learning methods
• Limitations in machine learning for spatio-temporal reasoning and learning; how far can machine learning go?
• Relation between causal reasoning and spatial and temporal reasoning
• Research and teaching challenges in spatio-temporal reasoning and learning

The list above is by no means exhaustive, as the aim is to foster the debate around all aspects of the suggested integration.

Application domains being addressed include, but are not limited to:

• Autonomous Vehicles and Drones
• Cognitive Robotics
• Spatial Computing for Design
• Computational Art
• (Cognitive) Vision
• Geographic Information Systems
• Smart Environments
• Healthcare

Submission

The submission link is available at: https://easychair.org/conferences/?conf=strl2024

Papers should be formatted according to the CEUR-ART style formatting guidelines here and submitted as a single PDF file.

We welcome submissions across the full spectrum of theoretical and practical work including research ideas, methods, tools, simulations, applications or demos, practical evaluations, and surveys.

Submissions that are 2 pages long (excluding references and appendices) will be considered for a short presentation, and submissions that are between 4 and 7 pages long (again, excluding references and appendices) will be considered for a regular presentation.

All papers will be peer-reviewed in a single-blind process and assessed based on their novelty, technical quality, potential impact, clarity, and reproducibility (when applicable).

Be mindful of the following dates:

• April 26, 2024: Workshop paper submission deadline
• May 31, 2024: Paper acceptance/rejection notification date
• June 7, 2024: Camera-ready submission deadline
• August 5, 2024: Workshop Date

Note: all deadlines are AoE (Anywhere on Earth).

Proceedings

The accepted papers will appear on the workshop website. We also intend to publish the workshop proceedings with CEUR-WS.org; this option will be discussed with the authors of accepted papers and is subject to the CEUR-WS.org preconditions. We note that, as STRL 2024 is a workshop, not a conference, submission of the same paper to conferences or journals is acceptable from our standpoint.

Workshop Organizers

• Parisa Kordjamshidi, Michigan State University, US (co-chair) https://www.cse.msu.edu/~kordjams/
• Jae Hee Lee, University of Hamburg, Germany (co-chair) https://jaeheelee.gitlab.io/
• Mehul Bhatt, Örebro University, Sweden (co-chair) https://mehulbhatt.org/
• Michael Sioutis, University of Montpellier, France (co-chair) https://msioutis.gitlab.io/
• Zhiguo Long, Southwest Jiaotong University, Chengdu, China (co-chair) https://zhiguolong.github.io/

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Date : 2024-08-26 => 2024-08-30
Lieu : Lyon, France

Conference EUSIPCO 2024, in Lyon (France) on August 26th-30th.

https://eusipcolyon.sciencesconf.org

Important dates: Special Session proposals: Jan 14, 2024 / Submission of Tutorial proposals: March 1, 2024 / Full paper submisson: March 3, 2024

—-

(english version at the end)

—

Cheres et chers collègues,

Au nom de l’Association européenne pour le traitement du signal (EURASIP), le comité d’organisation a le grand plaisir de vous inviter à la 32ème conférence européenne sur le traitement du signal, EUSIPCO 2024, qui se tiendra à Lyon, en France, du 26 au 30 août 2024.

EUSIPCO est la conférence phare d’EURASIP et propose un programme technique complet abordant tous les derniers développements de la recherche et de la technologie en traitement du signal. L’édition 2024 EUSIPCO rassemblera des conférenciers de premier plan du monde entier, et comprendra des sessions orales et affichées, des sessions plénières, des tutoriels et des workshop satellites. EUSIPCO2024 devrait attirer de nombreux chercheurs tant universitaires que de l’industrie. EUSIPCO 2024 prendra également une couleur particulière en mettant l’accent sur la recherche interdisciplinaire engagée vers les grands défis sociétaux.
Les orateurs principaux et les sessions spéciales seront choisis pour mettre l’accent sur ces enjeux.

L’appel à contributions est désormais disponible à l’adresse suivante
https://eusipcolyon.sciencesconf.org
https://eusipcolyon.sciencesconf.org/data/Eusipco2024_Call4Contributions.pdf

Merci de noter les dates importantes et ne pas hésiter pas à transmettre l’information à toute personne susceptible d’être intéressée par une contribution au programme scientifique d’Eusipco24 :

Special Session proposals: Jan 14, 2024
Submission of Tutorial proposals: March 1, 2024
Full paper submisson: March 3, 2024
Nous nous réjouissons de recevoir votre contribution et de vous accueillir à Lyon pour Eusipco24.

Le Comité d’Organisation d’Eusipco24
https://eusipcolyon.sciencesconf.org

Patrice Abry et Maria Sabrina Greco, General Chairs

—

Dear Colleagues,

On behalf of the European Association for Signal Processing (EURASIP), it is a great pleasure of the organizing committee to invite you to the 32nd European Signal Processing Conference, EUSIPCO 2024, to be held in Lyon, France, August, 26th-30th, 2024.

EUSIPCO is the flagship conference of EURASIP and offers a comprehensive technical program addressing all the latest developments in research and technology for signal processing. EUSIPCO 2024 will feature world-class speakers, oral and poster sessions, plenaries, exhibitions, demonstrations, tutorials, and satellite workshops, and is expected to attract many leading academic researchers and people from industry from all over the world. EUSIPCO 2024 will also have a specific flavour with a focus on interdisciplinary research geared toward major societal challenges. This will be highlighted by keynote speakers and special sessions.

The call for contributions are now available from
https://eusipcolyon.sciencesconf.org
https://eusipcolyon.sciencesconf.org/data/Eusipco2024_Call4Contributions.pdf

Please note the important dates and do not hesiatte to forward the information to any person that could be interested in contributing to Eusipco24 scientific program:

Special Session proposals: Jan 14, 2024
Submission of Tutorial proposals: March 1, 2024
Full paper submisson: March 3, 2024

We look forward to hosting your contribution and to welcoming you in Lyon for the Eusipco24.

Eusipco24 Organization Committee
https://eusipcolyon.sciencesconf.org

Patrice Abry et Maria Sabrina Greco, General Chairs

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Date : 2024-08-28
Lieu : Bayonne, France

****************************
CALL FOR PAPERS
DOING 2024: 5th International Workshop on Intelligent Data – From Data to Knowledge
****************************
August 28, 2024
Bayonne, France

In conjunction with ADBIS 2024

DOING@ADBIS 2024

Home – Technology Event

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IMPORTANT DATES
******************
Paper submission: 29 April, 2024 at 5 a.m. CET
Notification of acceptance: 8 June , 2024
Camera-ready due: 18 June , 2024
Workshop day: 8 August , 2024

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SUBMISSIONS
******************
DOING workshop accepts short (limited to 6-8 pages) and long (limited to 12 pages) papers. DOING reserves the right to accept as short papers those submitted as long, describing interesting and innovative ideas but still requiring further technical development. Papers should be written in English, formatted in Latex and present substantially original results. We adopt a double blind review policy: the papers submitted for review MUST NOT contain the authors’ names, affiliations, or any information that may disclose the authors’ identity. Authors should consult Springer’s authors’ guidelines and use their proceedings templates (you can download the templates available on the bottom of that page).

The workshop papers will be published by Springer in Communications in Computer and Information Science (CCIS). The authors of selected workshop papers will be invited to submit an extended version of their contributions to a special issue of an international journal.

ADBIS 2024 continues to participate in the Diversity and Inclusion (D&I) initiative of the Database community aiming to guide researchers in our community to adopt a more inclusive mindset in general toward different individuals.

**** Papers must be submitted via EASY CHAIR: https://easychair.org/conferences/?conf=adbis2024

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AIMS AND SCOPE
*******************

The workshop focuses on transforming data into information and then into knowledge. The idea is to gather researchers to discuss two main problems :

how to extract information from textual data and represent it in knowledge bases;
how to propose intelligent methods for handling and maintaining these databases with new forms of requests, including efficient, flexible, and secure analysis mechanisms, adapted to the user, and with quality and privacy preservation guarantees.

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TOPICS OF INTEREST
******************

We invite the submission of work-in-progress that address various aspects of information extraction from textual data, intelligent and efficient interrogation, and maintenance of (large) knowledge bases. The workshop welcomes submissions of theoretical, technical, experimental, methodological papers, application papers, position papers and papers on experience reports addressing – though not limited to – the following topics:

Artificial intelligence in databases and information systems
Data curation, annotation, and provenance
Data management and analytics
Data mining and knowledge discovery
Data models and query languages
Data quality and data cleansing
Data science (theory and techniques)
Context-aware and adaptive information systems
Constraints extraction from text
Natural language processing
Indexing, query processing and optimization
Information and knowledge extraction
Information integration
Information quality
Graph databases
Knowledge bases (querying, management, evolution and dynamics)
Machine learning for knowledge graph construction, completion, refinement
Machine learning for knowledge and information extraction, for instance, named entity disambiguation, sentiment analysis, relation extraction, or the detection of claims, facts and stances from unstructured documents
Machine Learning in NLP
Management of large volumes of data
Methodologies, models, algorithms, and architectures for applied data science
NLP for Digital Humanities
NLP & Knowledge Graphs
Privacy, trust and security in databases
Query processing and optimization
Question answering over knowledge graphs
Text databases

Preferred Application Domains (but not limited to).

Bio-sciences and healthcare
Environmental issues

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Annonce en lien avec l’Action/le Réseau :

Thème :

Techniques d’apprentissage machine pour l’analyse de données d’observation de la Terre

Présentation :

The MACLEAN workshop is hel in conjonction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD). The objective of this workshop is to supply an international forum where machine learning researchers and domain-experts can meet each other, in order to exchange, debate and draw short and long term research objectives around the exploitation and analysis of Earth Observation data via Machine Learning techniques.

Du : 2024-09-09

Au : 2024-09-09

Lieu : Vilnius, Lituanie

Site Web : https://sites.google.com/view/maclean24

Date : 2024-09-30 => 2024-10-03
Lieu : Toulouse, France

Dear all,

We are happy to announce the AISSAI Heterogeneous Data and Large Language Representation Models in Science Workshop that will be held in Toulouse (France) from September 30 to October 3, 2024.

We look forward to seeing you there.

Catherine Biscarat, Sylvain Caillou, Jan Stark, on behalf of the organizers

 

AISSAI Heterogeneous Data and Large Representation Models in Science Workshop

Toulouse (France), September 30 – October 3 2024

 FIRST ANNOUNCEMENT

 
 
 
The third workshop of the AISSAI trimester on “Artificial Intelligence for the two infinites” will be held in Toulouse (France) from September 30th to October 3rd, 2024. This workshop will be devoted to Heterogeneous Data and Large Representation Models in Science. 

This event is sponsored by the CNRS AISSAI center and hosted by the Laboratoire des 2 Infinis – Toulouse (L2IT).

Please find complete information on the scientific program, call for abstracts and registration on the workshop’s Indico website. Registration is free (but mandatory) and includes lunches and social events.

Scientific program

In recent years, we have witnessed remarkable transformations in the AI/ML landscape. Particularly in computer vision and natural language processing, there is a notable emergence of Large Representation Models (LRMs) trained on extensive datasets, often referred to as foundation models. These LRMs possess the capability to encode information at a high level of abstraction, enabling the training of models on multimodal data such as text, image, sound, video, and more. This improvement in how models represent objects augments significantly their ability to understand and make sense of the world.

In the realm of science, we expect a similar revolution, triggered by the integration of heterogeneous multimodal scientific data from various sensor systems or sources into LRMs. Scientific data are often heterogeneous and multimodal in nature, originating from various sensors in embedded systems (robotics, aerospace), from different detector subsystems or different instruments in fundamental physics, or from different signal sources in a scientific experiment in general. The models can combine representations from neural networks with symbolic representations integrating a priori knowledge of the scientific domain.

The aim of this workshop is to bring together scientists from different fields (just to list a few: computer sciences, cosmology, human sciences, mathematics, physics, robotics, statistics, etc.) and with different profiles (experimentalists, theorists, developers) to discuss these topics at the forefront of AI/ML research, fostering collaboration and innovation in this rapidly evolving field. 

The program is planed to be a mix of high-profile guest speaker presentations and contributed talks.

This workshop will delve into a range of topics, which include but are not limited to:

• Constructing machine learning models capable of learning from diverse data types.
• Managing multimodal data from varied sources, or heterogeneous data from scientific instruments that combine multiple detector technologies, for ML applications.
• Investigating contrastive embeddings tailored for heterogeneous and multi-modal scientific data alongside shared embedding representations.
• Exploring the integration of neuro-symbolic AI and multi-level representations.
• Mathematical modeling of combined representation.
• Exploring explainability and interpretability of Large Representation Models in the scientific context.
• Embracing frugality and size management in Large Representation Models.
• Possibly on a longer timescale, exploring numerical encodings for large language representations in scientific contexts. 

Website (Indico)

https://indico.in2p3.fr/event/33412/

Important dates

These dates may change.

• Registration opening: open now
• Abstract submission opening: open now
• Abstract submission dead-line: August 15th
• Abstract acceptance dead-line: August 31th
• Program release: September 7th
• Registration closing: September 15th
• Workshop start: September 30th

Scientific advisory committee

Sylvain Caillou (L2IT, IN2P3, CNRS/UT3) – chair
Alexandre Boucaud (APC, IN2P3, CNRS)
Tobias Golling (Université de Genève)
François Lanusse (Polymathic AI)
Daniel Murnane (Copenhagen University)
Thomas Oberlin (ISAE-SUPAERO, ANITI, Université Paul Sabatier)
Jan Stark (L2IT, IN2P3, CNRS/UT3)
Gordon Watts (Washington University)

Local organisation committee

Catherine Biscarat (L2IT, IN2P3, CNRS/UT3) – chair
Sylvain Caillou (L2IT, IN2P3, CNRS/UT3)
Jocelyne Gauthier (L2IT, IN2P3, CNRS/UT3)
Jan Stark (L2IT, IN2P3, CNRS/UT3)
Jeanette Thibaut (L2IT, IN2P3, CNRS/UT3)

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Date : 2024-10-01 => 2024-10-03
Lieu : Mila – Quebec AI Institute (Montréal, Canada) et hybride

* Cet événement de trois jours vise à explorer le potentiel de transformation des technologies langagières et leurs implications pour la société *

Grâce à des présentations, des débats et des sessions interactives, l’atelier vise à encourager la collaboration, l’échange de connaissances et la réflexion critique entre les chercheur·euse·s, les praticien·ne·s, les décideur·euse·s politiques et les parties prenantes de toutes les disciplines. En s’intéressant à la recherche de pointe, aux dilemmes éthiques et aux applications du monde réel, les participant·e·s acquerront une compréhension globale du paysage multiforme du NLP, de l’IA et des sciences cognitives, ainsi que de leurs implications profondes pour la transformation de la société.

L’événement est ouvert aux chercheur·euse·s en IA, en NLP et dans des domaines connexes, issus du monde universitaire et de l’industrie, ainsi qu’aux étudiant·e·s à la maîtrise et au doctorat dans tous les domaines de l’IA.

* Programmation *
+ La première journée est consacrée au NLP à l’ère de l’IA générative, où les participant⋅e⋅s examineront les dernières avancées dans les techniques de NLP alimentées par l’IA générative ou au-delà. Les discussions porteront sur les capacités, les défis et les considérations éthiques associés à ces technologies, offrant un aperçu de leur état actuel et de leurs futures trajectoires.
+ La deuxième journée, intitulée Rapprocher les esprits : Explorer l’intersection des sciences cognitives et de l’IA dans l’apprentissage des langues, explore la convergence des sciences cognitives et de l’IA dans la compréhension de l’acquisition du langage humain et la construction de systèmes linguistiques intelligents. Les orateur⋅trice⋅s et les participant⋅e⋅s se pencheront sur les théories cognitives de l’apprentissage des langues, les modèles informatiques inspirés de la cognition humaine et les applications pratiques de l’enseignement des langues et de la communication pilotés par l’IA.
+ La troisième journée, l’accent sera mis sur Comment les grands modèles de langage vont transformer la société, en examinant les implications sociétales plus larges des grands modèles de langage (LLM) et leur influence omniprésente dans divers domaines, notamment l’éducation, les médias, les soins de santé et la gouvernance. Les discussions porteront sur les considérations éthiques, les préjugés, la protection de la vie privée et la démocratisation de l’accès à l’information, dans le but de favoriser une réflexion critique et un déploiement responsable des grands modèles de langage au profit de la société.

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Date : 2024-10-03 => 2024-10-02
Lieu : CNRS headquartes, Paris 16

Dear colleagues,

It is with great pleasure that we invite you to three exciting events around “Optimization”, focus theme for CNRS Sciences informatiques in 2024.
–> more information about the events and links to further activities are available at https://www.ins2i.cnrs.fr/fr/loptimisation-au-coeur-des-defis-des-sciences-informatiques
–> Default language for the October 2 and 3 events is French, while English will be default language on October 4
–> Spots are limited for all three events and will be given on a first come, first served basis. In all fairness (and to avoid food waste), please register only if you are sure to attend (and keep us informed if you have to cancel your participation)

(1) October 2: Journée Industrielle du GDR ROD et RT Optimisation (Sorbonne Université – Jussieu – Paris 5ième)
Keynotes by Olivier Juan (EDF R&D), Tristan Rigaut (Schneider Electric), Jean-Charles Billaut (LIFAT, Université de Tours), Adam Ouorou (Orange Labs), Alexandre Marié (Artelys), Gautier Avril (Purecontrol)
–> Further information and registration: http://gdrro.lip6.fr/?q=node/334

(2) October 3: L’optimisation : au cœur des défis des sciences informatiques (CNRS headquarter – Paris 16ième)
The big conference for the larger public on October 3 at the CNRS headquarter (Paris 16ième)
Keynotes: Jérôme BOLTE, Claire MATHIEU, Axel PARMENTIER, and Gabriel PEYRÉ
Flash presentations by: Simon APERS, Céline COMTE, Sophie HUIBERTS, Martin KREJCA, Clément W. ROYER, David SAULPIC, Sandra ULRICH-NGUEVEU and 3 industrial speakers
–> Further information and registration: https://www.ins2i.cnrs.fr/fr/cnrsinfo/conference-loptimisation-au-coeur-des-defis-des-sciences-informatiques

(3) October 4: Scientific conference (CNRS headquarter – Paris 16ième)
In cooperation with 9 GDRs of CNRS Sciences informatiques and the thematic network “optimization” of CNRS Mathématiques, we’ll come together to discuss the role of optimization in the various sub-disciplines
Keynote: Jean-Bernard LASSERRE
Presentations for the GDRs: BIMM (Annie Chateau), GPL (Clément Quinton), IASIS (Laure Blanc-Féraud), IFM (speaker to be confirmed), IG-RV (Julie Digne), MaDICS (Laure Berti-Equille), RADIA (Christophe Lecoutre), ROD (Michaël Poss), RSD (Christelle Caillouet), RT optimisation (Jean-Baptiste Caillaux)
The presentations will be complemented by discussions around the optimization landscape in France (current situation and our ambition) and breakouts around (i) industrial vs. academic research (ii) ecological aspects of optimization, (iii) optimization and ethics
–> Further information and registration: https://www.ins2i.cnrs.fr/en/scientific-day-optimization

We look forward to welcoming you at these events.

Kind regards,
the scientific organizing committee:

Claudia D’Ambrosio, Carola Doerr, Jérôme Malick, Alantha Newmann, Edouard Pauwels

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Date : 2024-10-07 => 2024-10-11
Lieu : SCAI/ISCD, Sorbonne Université, 4 place Jussieu, 75005 Paris, France

ML4Oceans 2024 – 2nd edition!

The use of artificial intelligence is now crucial for environmental and climate issues, including oceanography. In this context, SCAI, ISCD and the Institut de l’Océan of Sorbonne Université joined their forces, together with the support of EUR-IPSL, to offer a transdisciplinary school for PhD candidates and post-doctoral researchers. 20 candidates will be selected according to their academic background, their research subject & their motivation to participate in this school.

The objective: to acquire knowledge and skills in AI applied to oceanography (marine biology – omics, biogeochemistry, acoustics, imagery).

Practical information

The school will take place in the seminar room of SCAI, the Sorbonne Center for Artificial Intelligence. It is located on the Pierre and Marie Curie Campus of Sorbonne University, 4 place Jussieu (métro Jussieu), 75005 Paris, France. Lectures will be given in English.

Programme

The school will be from 9h to 17h or 18h, from Monday to Friday. Each day, you will have two classes of 1h30 each in the morning, by experts in their field: one on an oceanography topic and one on a machine learning topic. In the afternoon, you will have a tutored practical lab, in a dedicated computing environment, to apply a machine learning algorithm on real oceanic data. This direct application of the morning class will encompass coding, training, and applying a model.

Tentative programme:

• Monday 7th October: Introductions to the school, the programming language (Python and PyTorch) and the coding environment.
• Tuesday 8th October: Oceano: Marine omics. ML: Tree based models. Lab: Predicting carbon concentration genomic potential using multivariate gradient boosted trees.
• Wednesday 9th October: Oceano: Biogeochemical Argo floats. ML: Multilayer Perceptron. Lab: Deriving scarcely observed biogeochemical variables from profiles of common Argo ones using an MLP.
• Thursday 10th October: Oceano: Passive acoustics. ML: Convolutional neural networks. Lab: Classifying marine mammals sounds using CNNs.
• Friday 11th October: Oceano: Plankton imaging. ML: CNNs for object detection and segmentation. Lab: Instance segmentation of planktonic organisms from images using CNNs.

Application procedure

Please apply online before the 27th of June 2024:

LINK TO THE REGISTRATION FORM : https://framaforms.org/ml4oceans-school-2024-1713121567

Candidates will be selected using the following criteria: adequation between the school’s thematics and the candidate’s research project, minimum skill requirement, motivation for the ML4Oceans school. Candidates from different backgrounds are encouraged to apply.

The outcome of the selection procedure will be communicated to the candidates mid-July.

Speakers

Olivier Adam, IJLRDA, SU
Lucie Bittner, ISYEB, SU
Dorian Cazau, LabSTICC, ENSTA Bretagne
Anastase Charantonis, LaMME/LOCEAN, ENSIIE/INRIA
Hervé Claustre, LOV, SU/CNRS
Jean-Olivier Irisson, LOV, SU
Jérémy Fix, CentraleSupélec, LORIA
Raphaëlle Sauzède, LOV-IMEV, SU

Organising committee

Sakina-Dorothée Ayata, LOCEAN, SU
Lucie Bittner, ISYEB, SU
Anastase Charantonis, LaMME/LOCEAN, ENSIIE/INRIA
Jean-Olivier Irisson, LOV, SU

Please contact sakina-dorothee.ayata@locean.ipsl.fr for any questions.

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Date : 2024-10-14 => 2024-10-18
Lieu : Sophia Antipolis

Cette édition IA2 2024 concerne le rôle de l’intelligence artificielle en tant que facteur déterminant pour l’avenir de l’humanité, car elle contribue avec ses applications à transformer considérablement la vie des individus et à avoir un impact sur les communautés humaines. Plus en particulier, cette école a pour objectif de traiter les questions suivantes : Quel rôle l’IA joue-t-elle dans les relations entre le citoyen et l’administration ou le gouvernement ? Qui utilise cette technologie et dans quel but ? Comment l’utilisation de l’IA influence-t-elle les relations de pouvoir dans l’élaboration des politiques et la confiance des citoyens dans les institutions démocratiques ?

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Date : 2024-10-15
Lieu : Université Paris Dauphine-PSL

Journée éducative sur la technologie Blockchain pour les étudiants, les universitaires, les entreprises et les formateurs professionnels.

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