ICLR 2023 Schedule

In-Person Oral presentation / top 5% paper

Mon May 01 10:10 AM -- 10:20 AM (CEST) @ Auditorium None

Token Merging: Your ViT But Faster

In Oral 1 Track 1: Deep Learning and representational learning I

Daniel Bolya · Cheng-Yang Fu · Xiaoliang Dai · Peizhao Zhang · Christoph Feichtenhofer · Judy Hoffman

In-Person Oral presentation / top 25% paper

Mon May 01 10:20 AM -- 10:30 AM (CEST) @ Auditorium None

TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second

In Oral 1 Track 1: Deep Learning and representational learning I

Noah Hollmann · Samuel Müller · Katharina Eggensperger · Frank Hutter

In-Person Oral presentation / top 25% paper

Mon May 01 10:30 AM -- 10:40 AM (CEST) @ Auditorium None

Learning Group Importance using the Differentiable Hypergeometric Distribution

In Oral 1 Track 1: Deep Learning and representational learning I

Thomas Sutter · Laura Manduchi · Alain Ryser · Julia E Vogt

In-Person Oral presentation / top 25% paper

Mon May 01 10:40 AM -- 10:50 AM (CEST) @ Auditorium None

Neural Networks and the Chomsky Hierarchy

In Oral 1 Track 1: Deep Learning and representational learning I

Gregoire Deletang · Anian Ruoss · Jordi Grau-Moya · Tim Genewein · Li Kevin Wenliang · Elliot Catt · Chris Cundy · Marcus Hutter · Shane Legg · Joel Veness · Pedro Ortega

In-Person Oral presentation / top 5% paper

Mon May 01 10:50 AM -- 11:00 AM (CEST) @ Auditorium None

Learning on Large-scale Text-attributed Graphs via Variational Inference

In Oral 1 Track 1: Deep Learning and representational learning I

Jianan Zhao · Meng Qu · Chaozhuo Li · Hao Yan · Qian Liu · Rui Li · Xing Xie · Jian Tang