Generative Adversarial Symmetry Discovery
- Jianke Yang
- Robin Walters
- et al.
- 2023
- ICML 2023
Conference paper
Publications
ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction
- Wang Zhang
- Tsui-Wei Weng
- et al.
- 2023
- ICML 2023
Conference paperLearning Prescriptive ReLU Networks
- Wei Sun
- Asterios Tsiourvas
- 2023
- ICML 2023
Conference paperProper Scoring Rules for Survival Analysis
- Hiroki Yanagisawa
- 2023
- ICML 2023
Conference paperPrometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning
- Zhuqing Liu
- Xin Zhang
- et al.
- 2023
- ICML 2023
Conference paperMultiRobustBench: Benchmarking Robustness Against Multiple Attacks
- Sihui Dai
- Saeed Mahloujifar
- et al.
- 2023
- ICML 2023
Conference paperReprogramming Pretrained Language Models for Antibody Sequence Infilling
- Igor Melnyk
- Vijil Chenthamarakshan
- et al.
- 2023
- ICML 2023
Conference paperWhich Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression
- Yihao Xue
- Siddharth Joshi
- et al.
- 2023
- ICML 2023
Conference paperIdentification of the Adversary from a Single Adversarial Example
- Minhao Cheng
- Rui Min
- et al.
- 2023
- ICML 2023
Conference paperPatch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks
- Mohammed Nowaz Rabbani Chowdhury
- Shuai Zhang
- et al.
- 2023
- ICML 2023
Conference paper