elias-ai

Joint ELIAS-ELISE Flagship Workshop
2024-02-07 - 2024-02-08 | NH Collection Frankfurt Spin Tower Hotel, Güterplatz 1, Frankfurt, 60237, Germany
Theme
This workshop aims to initiate tangible actions supported by ELIAS and ELISE to empower the next generation of talent, establish foundational models, and foster startups. Key measures the projects seek to align on include an annual meeting on open source foundation models and sciencepreneurship, a European graduate project programme, a pan-EU incubation programme, and a call for sciencepreneur fellows and units akin to the European Lab for Learning and Intelligent Systems (ELLIS) network’s calls for fellows and units.

Location
Our venue is the NH Collection Frankfurt Spin Tower Hotel, Frankfurt, Germany.

Programme

Event Programme

Time
Activity

12:00 - 13:00
Registration & Coffee

13:00 - 13:15
Official Start of Workshop & Welcome by Matthias Bethge (Tübingen AI Center & ELLIS Fellow)

13:15 - 14:50
Speakers: Yann LeCun (Meta), Katharina Frey (Swiss Foreign Ministry & ICAIN), Laura Morselli (CINECA & EuroHPC), Jenia Jitsev (LAION-ELLIS Member)

14:50 - 15:30
Coffee break

15:30 - 17:00
Speakers: Ce Zhang (Together AI), Samuel Weinbach (IPAI Aleph Alpha), Daniel Naeff (Swiss AI)

17:00 - 18:00
Open discussion on Annual Meeting for Open Source community, spotlight presentations (Moderated by Matthias Bethge)

18:00 - 20:00
Joint dinner

20:00 - 20:45
Intro about ELIAS and briefing on ELIAS measures (Nicu Sebe - ELIAS Coordinator & ELLIS Fellow)

20:45
Time for open discussions at the hotel bar

09:00 - 09:05
Welcome (Matthias Bethge)

09:05 - 09:20
Gregor von Dulong: “Learnings from building and scaling entrepreneurship education at HPI”

09:20 - 09:30
Wieland Brendel (ELLIS Scholar): “Polybot”

09:30 - 10:00
Isabelle Siegrist: “Building a pan-European Accelerator”

10:00 - 12:00
Breakout groups on:
- How to build the ELIAS Innovation Alliance (EIA), define the narrative, and set up a call for sciencepreneur fellows, units, graduation projects (Matthias Bethge & Arnout Devos)
- How to set up an annual meeting for AI (Daniel Naeff & Wieland Brendel)
- How to set up a Pan-EU incubation program for AI Startups? (Isabelle Siegrist)

12:00 - 13:30
Joint lunch

13:30 - 16:00
Further spotlight presentations:
- Steffen Schneider (KI macht Schule)
- Le Viet (La Famiglia)
- Beyza Ermis (Cohere AI)
Presentation and discussion of breakout group results.
Discussion of White paper

For more details, visit our website.

This workshop is co-organised with ELISE – European Network of AI Excellence Centres, funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 951847.

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Details
Start: February 7
End: February 8
Event Category: Workshops
Event Tags: eliasproject, elise, ellis, foundationmodels, sciencepreneurship

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Organiser
University of Tübingen

Venue
Location: NH Collection Frankfurt Spin Tower Hotel
Güterplatz 1, Frankfurt, 60237 Germany

View Venue Website

© 2024 NH Collection Frankfurt Spin Tower Hotel. All rights reserved.

AI Excellence Lecture on Deep learning and Process Understanding for Data-Driven Earth System Science
2024-01-30 17:00 - 18:00 (Europe/Rome) | ONLINE
Abstract: For a better understanding of the Earth system we need a stronger integration of observations and (mechanistic) models. Classical model-data integration approaches start with a model structure and try to estimate states or parameters via data assimilation and inverse modelling, respectively. Sometimes, several model structures are employed and evaluated, e.g. in Bayesian model averaging, but still parametric model structures are assumed. Recently, Reichstein et al. (2019) proposed a fusion of machine learning and mechanistic modelling approaches into so-called hybrid modelling. Ideally, this combines scientific consistency with the versatility of data driven approaches and is expected to allow for better predictions and better understanding of the system, e.g. by inferring unobserved variables. This talk will elaborate on developments of this concept and illustrate its promise but also challenges with examples on biosphere-atmosphere exchange, and carbon and water cycles from the ecosystem to the global scale.
Lecturer: Prof. Dr. Markus Reichstein is Director of the Biogeochemical Integration Department at the Max-Planck-Institute for Biogeochemistry. His main research interests revolve around the response and feedback of ecosystems (vegetation and soils) to climatic variability with an Earth system perspective. Of specific interest is the interplay of climate extremes with ecosystem and societal resilience. He is addressing these topics with a combination of artificial intelligence and system modelling approaches to exploit the wealth of experimental, ground- and satellite-based Earth observations.
About AIDA: The four ICT-48 networks (AI4Media, ELISE, HumanE-AI NET, TAILOR) and the VISION project joined forces and, under the joint initiative of VISION and AI4Media, founded a new joint instrument to support a world-level AI education and research programme.
The International AI Doctoral Academy (AIDA) has been created for offering access to knowledge and expertise and attracting PhD talents in Europe. AIDA offers free, top-notch AI Excellence Lecture Series, featuring senior experts and promising juniors, encouraging active participation, and providing easy access through multiple channels
🔗 For more information: Artificial Intelligence Doctoral Academy – AI Excellence Lecture Series

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Details
Date: January 30
Time: 17:00 - 18:00
Event Category: Lectures & Seminars

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Deep Learning and Process Understanding for Data-Driven Earth System Science

Venue
Location: ONLINE

Organiser
AIDA – Artificial Intelligence Doctoral Academy
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© 2024 AIDA – Artificial Intelligence Doctoral Academy. All rights reserved.

ELLIS Multimodal Learning Systems Workshop on Multimodal Foundation Models
2024-01-17 - 2024-01-19 | Mathematisches Forschungsinstitut Oberwolfach (MFO), Schwarzwaldstraße 9-11, Oberwolfach-Walke, 77709, Germany
Theme

Multimodal foundation models are a revolutionary class of AI models that provides impressive abilities to generate content (text, images, sound, videos, protein structures, and more), and do so by interactive prompts in a seemingly creative manner. These foundation models are often autoregressive, self-supervised, transformer-based models that are pre-trained on large volumes of data, typically collected from the web. They already form the basis of all state-of-the-art systems in computer vision and natural language processing across a wide range of tasks and have shown impressive few-shot learning abilities. The perceived intelligence and adaptability of models like ChatGPT, Stable Diffusion, Gemini, and GPT4 impress, but their aptitude to produce inaccurate, misleading, or false information (and present it confidently and convincingly) makes them unsuitable for any task of importance and poses serious societal concerns. In this workshop we present recent advances on multimodal foundation models from academia and industry and discuss their impact and implications moving forward.

Location

The workshop is hosted at the Mathematisches Forschungsinstitut Oberwolfach (MFO). Accommodation and meals will take place in Hotel Hirschen, which is within walking distance of the MFO.

Event Programme

Programme

Wednesday January 17

15:00 - 19:00
Arrival of attendees, time for socializing and discussion

19:00 - 22:00
Opening dinner at Hotel Hirschen

Thursday January 18

08:00 - 09:30
Breakfast at Hotel Hirschen

09:30 - 11:00

Morning Session I: Foundation Models (Chair: Yiannis Kompatsiaris)
FoMO without FOMO by Karteek Alahari (Inria)
Towards 3D Human Foundation Models by Cristian Sminchisescu (Google)
What multimodal foundation models cannot perceive by Cees Snoek (University of Amsterdam)
Are Foundation Models the tool for Social Embodied AI? by Xavier Alameda-Pineda (Inria)

11:00 - 11:30
Coffee break

11:30 - 12:30

Morning Session II: Vision & Language (Chair: Dima Damen)
Vocabulary-free Image Classification by Elisa Ricci (University of Trento)
Coreference resolution in narrated images by Hakan Bilen (The University of Edinburgh)
Vision-Language Self-Supervised Learning by Shaogang Gong (Queen Mary, University of London)

12:30 - 14:00
Lunch break at Hotel Hirschen

14:00 - 15:30

Afternoon Session I: Generative AI (Chair: Karteek Alahari)
Images & text: alignment, generation and compression by Jakob Verbeek (Meta)
Measuring the Quality of Generative Neural Networks - An Unsolved Problem by Juergen Gall (University of Bonn)
Controllable generation for Analysis and Synthesis by Ioannis Patras (Queen Mary, University of London)
Improving Fairness using Vision-Language Driven Image Augmentation by Nicu Sebe (University of Trento)

15:30 - 16:00
Coffee break

16:00 - 17:00

Afternoon Session II: Multimodality (Chair: Xavier Alameda-Pineda)
Multi-modality in Egocentric Vision - Contradictory and complementary signals by Dima Damen (University of Bristol)
Multimodal LLMs for Document Understanding by Dimosthenis Karatzas (Universitat Autónoma de Barcelona)
Large Multimodal Models for Media and Journalism by Yiannis Kompatsiaris (Information Technologies Institute, CERTH)

17:00 - 18:30
Discussion Session (Chairs: Cees Snoek & Nicu Sebe)

19:00 - 22:00
Dinner at Hotel Hirschen

Friday January 19

08:00 - 10:00
Breakfast at Hotel Hirschen

10:00 onwards
Departure

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Details
Start: January 17
End: January 19
Event Category: Workshops

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Multimodal FoMO Workshop
Organiser
ELLIS, ELISE & ELIAS

Venue
Location: Mathematisches Forschungsinstitut Oberwolfach (MFO)
Schwarzwaldstraße 9-11, Oberwolfach-Walke, 77709 Germany
Phone: +49 (0) 7834 979-0
View Venue Website

© 2024 ELLIS, ELISE & ELIAS. All rights reserved.

AI Excellence Lecture on Hybrid & Causal Machine learning in the Earth sciences
2024-01-16 17:00 - 18:00 | ONLINE
Abstract: Most problems in Earth sciences aim to do inferences about the system, where accurate predictions are just a tiny part of the whole problem. Inferences mean understanding variables relations, deriving models that are physically plausible, that are simple parsimonious, and mathematically tractable. While machine learning models excel as approximators, they often disregard fundamental physics laws, compromising consistency and confidence. To address these challenges, we propose exploring the interplay between domain knowledge and machine learning. Physics-aware and hybrid machine learning models are seen as necessary steps toward understanding the data-generating process, with causality offering significant advancements. I will discuss recent hybrid and causal machine learning methodologies to attain consistent and explainable results. This work outlines a collective, long-term AI agenda for developing algorithms that can discover knowledge in the Earth system.
Lecturer: Professor Gustau Camps-Valls is a Full Professor in Electrical Engineering at the Universitat de Valencia. He is an expert in machine learning algorithms for geosciences and remote sensing data analysis, having published extensively. He has a Ph.D. in Physics and is an IEEE Distinguished Lecturer. He has received two European Research Council (ERC) grants and holds a Hirsch’s index h=88 (Google Scholar). He is also a Highly Cited Researcher since 2020. Gustau has achieved significant recognition with numerous awards and honors, including IEEE Fellow (2018), ELLIS Fellow (2019), Fellow of the European Academy of Sciences (EurASc), the Academia Europeae (AE), and the Asia-Pacific Artificial Intelligence Association (AAIA) all in 2021.
About AIDA: The four ICT-48 networks (AI4Media, ELISE, HumanE-AI NET, TAILOR) and the VISION project joined forces and, under the joint initiative of VISION and AI4Media, founded a new joint instrument to support a world-level AI education and research programme.
The International AI Doctoral Academy (AIDA) has been created for offering access to knowledge and expertise and attracting PhD talents in Europe. AIDA offers free, top-notch AI Excellence Lecture Series, featuring senior experts and promising juniors, encouraging active participation, and providing easy access through multiple channels
🔗 For more information: Artificial Intelligence Doctoral Academy – AI Excellence Lecture Series

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Details
Date: January 16
Time: 17:00 - 18:00
Event Category: Lectures & Seminars

AI
ML

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Hybrid Causal Machine Learning in the Earth Sciences

Venue
Location: ONLINE

Organiser
AIDA – Artificial Intelligence Doctoral Academy
View Organiser Website

© 2024 AIDA – Artificial Intelligence Doctoral Academy. All rights reserved.
