Cheung, Brian

17 publications

NeurIPS 2025 Training the Untrainable: Introducing Inductive Bias via Representational Alignment Vighnesh Subramaniam, David Mayo, Colin Conwell, Tomaso Poggio, Boris Katz, Brian Cheung, Andrei Barbu

NeurIPSW 2024 ImageNet-RIB Benchmark: Large Pre-Training Datasets Don't Guarantee Robustness After Fine-Tuning Jaedong Hwang, Brian Cheung, Zhang-Wei Hong, Akhilan Boopathy, Pulkit Agrawal, Ila R Fiete

ICML 2024 Position: The Platonic Representation Hypothesis Minyoung Huh, Brian Cheung, Tongzhou Wang, Phillip Isola

NeurIPSW 2024 Workshop Submission: Towards Making Untrainable Networks Trainable Vighnesh Subramaniam, Tomaso A Poggio, Boris Katz, Brian Cheung, Andrei Barbu

WACV 2023 Compact and Optimal Deep Learning with Recurrent Parameter Generators Jiayun Wang, Yubei Chen, Stella X. Yu, Brian Cheung, Yann LeCun

NeurIPSW 2023 How to Guess a Gradient Utkarsh Singhal, Brian Cheung, Kartik Chandra, Jonathan Ragan-Kelley, Joshua B. Tenenbaum, Tomaso A Poggio, Stella X. Yu

ICML 2023 Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks Minyoung Huh, Brian Cheung, Pulkit Agrawal, Phillip Isola

ICML 2023 System Identification of Neural Systems: If We Got It Right, Would We Know? Yena Han, Tomaso A Poggio, Brian Cheung

TMLR 2023 The Low-Rank Simplicity Bias in Deep Networks Minyoung Huh, Hossein Mobahi, Richard Zhang, Brian Cheung, Pulkit Agrawal, Phillip Isola

ICLR 2022 Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations Rumen Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic

NeurIPSW 2022 System Identification of Neural Systems: If We Got It Right, Would We Know? Yena Han, Tomaso Poggio, Brian Cheung

ICML 2020 Cautious Adaptation for Reinforcement Learning in Safety-Critical Settings Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman

ICLR 2019 Meta-Learning Update Rules for Unsupervised Representation Learning Luke Metz, Niru Maheswaranathan, Brian Cheung, Jascha Sohl-Dickstein

NeurIPS 2019 Superposition of Many Models into One Brian Cheung, Alexander Terekhov, Yubei Chen, Pulkit Agrawal, Bruno Olshausen

NeurIPS 2018 Adversarial Examples That Fool Both Computer Vision and Time-Limited Humans Gamaleldin Elsayed, Shreya Shankar, Brian Cheung, Nicolas Papernot, Alexey Kurakin, Ian Goodfellow, Jascha Sohl-Dickstein

ICLR 2017 Emergence of Foveal Image Sampling from Learning to Attend in Visual Scenes Brian Cheung, Eric Weiss, Bruno A. Olshausen

ICLR 2015 Discovering Hidden Factors of Variation in Deep Networks Brian Cheung, Jesse A. Livezey, Arjun K. Bansal, Bruno A. Olshausen