The 2nd Bayes-Duality Workshop 2024

About Program Participants Workshop 2023

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”.

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 26 one hour invited talks including 4 on the CREST project.
  • In addition, we will also have 10 hours of tutorials and four 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
  • Koiichi Tojo
  • Asuka Takatsu, Tokyo Metropolitan University/RIKEN
  • Kei Hagihara, Keio University
  • Kanji Inui, Keio 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