Improving Transformation Invariance in Contrastive Representation Learning. - Adam Foster 001; Rattana Pukdee; Tom Rainforth (ICLR, 2021)

Sharp asymptotics on the compression of two-layer neural networks. - Mohammad Hossein Amani; Simone Bombari; Marco Mondelli; Rattana Pukdee; Stefano Rini (ITW, 2022)

Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games. - Maria-Florina Balcan; Rattana Pukdee; Pradeep Ravikumar; Hongyang Zhang 001 (AISTATS, 2023)

Label Propagation with Weak Supervision. - Rattana Pukdee; Dylan Sam; Pradeep Kumar Ravikumar; Nina Balcan (ICLR, 2023)

Reliable learning in challenging environments. - Maria-Florina Balcan; Steve Hanneke; Rattana Pukdee; Dravyansh Sharma (NeurIPS, 2023)

Learning with Explanation Constraints. - Rattana Pukdee; Dylan Sam; J. Zico Kolter; Maria-Florina Balcan; Pradeep Ravikumar (NeurIPS, 2023)

Reliable Learning for Test-time Attacks and Distribution Shift. - Maria-Florina Balcan; Steve Hanneke; Rattana Pukdee; Dravyansh Sharma (CoRR, 2023)

Spectrally Transformed Kernel Regression. - Runtian Zhai; Rattana Pukdee; Roger Jin; Maria-Florina Balcan; Pradeep Kumar Ravikumar (ICLR, 2024)

Bayesian Neural Networks with Domain Knowledge Priors. - Dylan Sam; Rattana Pukdee; Daniel P. Jeong; Yewon Byun; J. Zico Kolter (CoRR, 2024)

On the Consistent Recovery of Joint Distributions from Conditionals. - Mahbod Majid; Rattana Pukdee; Vishwajeet Agrawal; Burak Varici; Pradeep Kumar Ravikumar (AISTATS, 2025)

Learning from weak labelers as constraints. - Vishwajeet Agrawal; Rattana Pukdee; Maria-Florina Balcan; Pradeep Kumar Ravikumar (ICLR, 2025)