The 2nd Bayes-Duality Workshop 2024

About Program Participants

This is the second edition of the Bayes-duality workshop focusing on the development of AI that learns adaptively, robustly and continuously, like humans. The main goal of the meeting is to discuss (and refine) the long-term goals of the project and foster collaborations among the attendees. Part 1 of the workshop is open to public (through live streaming) and will feature talks, tutorials, and discussion by world-leading researchers working on related topics. Part 2 and 3 will be closed meetings exclusively for the collaborators of the Bayes-duality project.

Similarly to the previous edition, we hope that the proposed activities help attendees increase their research's impact, outreach and help them network. This workshop is supported by RIKEN-AIP subsidy budget and the JST CREST Grant JPMJCR2112 on “A new Bayes-duality principle for adaptive, robust, and lifelong learning of AI systems”.

In-person attendance is limited to RIKEN-AIP researchers and invited guests, but all talks in Part 1 (June 12-21) will be streamed live and zoom link can be obtained by registering at doorkeeper.

About Talks and Tutorials

  • Invited talks will be of 40 mins length + 20 mins Q&A. Shorter talks and more discussions are encouraged.
  • Part 1 hosts 25 invited talks (each 1 hour) including 4 on the CREST project.
  • In addition, we will also have 7 hours of tutorials and 3 panel discussions of 1 hour 30 minutes.

Participants

Invited Speakers (in alphabetical order)
Adam White
Adam White

University of Alberta, Canada

Alexander Immer
Alexander Immer

ETH, Switzerland

Arindam Banerjee
Arindam Banerjee

University of Illinois Urbana-Champaign, US

Daiki Chijiwa
Daiki Chijiwa

NTT Corporation, Japan

Name
Ehsan Amid

Google DeepMind, US

Eugene Ndiaye
Eugene Ndiaye

Apple, France

Frank Nielsen
Frank Nielsen

Sony Computer Science Laboratories, Japan

Jonghyun Choi
Jonghyun Choi

Seoul National University, South Korea

Juho Lee
Juho Lee

KAIST, South Korea

Haavard Rue
Haavard Rue

KAUST, Saudi Arabia

Hossein Mobahi
Hossein Mobahi

Google Research, US

Martin Mundt
Martin Mundt

TU Darmstadt, Germany

Matt Jones
Matt Jones

University of Colorado, US

Nico Daheim
Nico Daheim

TU Darmstadt, Germany

Razvan Pascanu
Razvan Pascanu

Google DeepMind, US

Rupam Mahmood
Rupam Mahmood

University of Alberta, Canada

Sarath Chandar
Sarath Chandar

École Polytechnique de Montréal, Canada

Siddharth Swaroop
Siddharth Swaroop

Harvard University, US

Tom Rainforth
Tom Rainforth

University of Oxford, UK

Vincent Fortuin
Vincent Fortuin

Helmholtz AI, Germany

Yingzhen Li
Yingzhen Li

Imperial College London, UK

Zelda Mariet
Zelda Mariet

Bioptimus, US

ABI Team, RIKEN
  • Emtiyaz Khan
  • Thomas Möllenhoff
  • Hugo Monzón
  • Keigo Nishida
  • Zhedong Liu
  • Christopher Anders
  • Dharmesh Tailor, ABI Student Trainee/University of Amsterdam, Netherlands
Math-Science Team, RIKEN
  • Kenichi Bannai, Keio University/RIKEN
  • Eren Mehmet Kıral, Keio University
  • Koichi Tojo
  • Asuka Takatsu, Tokyo Metropolitan University/RIKEN
  • Kei Hagihara, Keio University
  • Kanji Inui, Doshisha University
HPC Team, Tokyo Tech
  • Rio Yokota
  • Cong Bai
  • Clément Bazan
  • Eiki Shimizu
  • Satoki Ishikawa
Stat-Theory Team, INRIA Grenoble Rhône-Alpes, France
  • Julyan Arbel
  • Tam Le Minh
  • Jacopo Iollo
Attendees
  • Navish Kumar, University of Basel, Switzerland
  • Roshni Kamath, TU Darmstadt, Germany
  • Yuesong Shen, TU Munich, Germany
  • Srijith Prabhakaran Nair Kusumam, IIT Hyderabad, India
  • Avni Rajpal, IIT Hyderabad, India
  • Rishabh Karnad, IIT Hyderabad, India
  • Seongwon Cho, Yonsei University, South Korea
  • Minhyuk Seo, Yonsei University, South Korea
  • Falko Helm, TU Darmstadt, Germany
  • Daniel Augusto Ramos Macedo Antunes de Souza, University College London, UK
  • Mariko Iinuma, Google DeepMind, US
  • Saurav Jha, UNSW Sydney, Australia
  • Jessica Hoffmann, Google Research, US
  • Kai Arulkumaran, Araya, Japan
  • Claire Vernade, University of Tübingen

Program

[The detailed program] [PDF version for printing]
June 12 June 13 June 14 June 17 June 18 June 19 June 20 June 21
10:00-11:00 Masashi Sugiyama

Vincent Fortuin
Haavard Rue Frank Nielsen Martin Mundt Emtiyaz Khan (CREST) Razvan Pascanu Tutorial: Optimization for DL Yingzhen Li
11:00-11:30 Break Break Break Break Break Break Break
11:30-12:30 Juho Lee Tutorial: Convex Duality Jonghyun Choi Siddharth Swaroop Thomas Möllenhoff (CREST) Rupam Mahmood Hossein Mobahi Daiki Chijiwa
12:30-14:00 Lunch Lunch Lunch Lunch Lunch Lunch Lunch Lunch
14:00-15:00 Tutorial: Conformal Prediction Tutorial: Bayesian Learning Rule Tutorial: Continual Learning Rio Yokota Talks on Memory, Model Merging, Continual Learning Sarath Chandar Arindam Banerjee Zelda Mariet
15:00-16:00 Eugene Ndiaye Tutorial: Experiment Design Poster Session Tom Rainforth Poster Session Break*
16:00-16:30 Break Break Break Break Break Break Break Ehsan Amid
16:30-17:30 Alex Immer Matt Jones Panel 1: Uncertainty in AI Poster Session Panel 2: Lifelong Learning Adam White Poster Session Panel 3: Future of AI
17:30-18:00
18:00- Dinner/Drinks Speakers Dinner Dinner/Drinks

* Due to a fire/earthquake drill from 15:30 to 16:10, the regular Break will start earlier. Last talk will begin once the drill is over, and the panel will follow a bit later than scheduled.

Each speaker can join Zoom through the link sent to them by email. This link allows you to join as a ‘co-host’. Please do not try to use other links (e.g., the one in doorkeeper). Contact Hugo Monzon, Cong Bai, or Clément Bazan, in case of zoom trouble.

Organizing Team

  • Administrative affairs: Tomoko Hiramitsu, Harumi Seo, Ikuko Tsumura
  • Webpage Design: Hugo Monzón
  • Talk/Speaker Assistance: Cong Bai, Clément Bazan, Satoki Ishikawa
  • Poster Session Assistance: Koichi Tojo, Kanji Inui, Kenichi Bannai
  • Socials: Keigo Nishida, Dharmesh Tailor, Zhedong Liu