Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression. - Yihao Xue; Siddharth Joshi 004; Eric Gan; Pin-Yu Chen; Baharan Mirzasoleiman (ICML, 2023)

Inference and Interference: The Role of Clipping, Pruning and Loss Landscapes in Differentially Private Stochastic Gradient Descent. - Lauren Watson; Eric Gan; Mohan Dantam; Baharan Mirzasoleiman; Rik Sarkar (CoRR, 2023)

Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias. - Yu Yang 007; Eric Gan; Gintare Karolina Dziugaite; Baharan Mirzasoleiman (AISTATS, 2024)

Investigating the Benefits of Projection Head for Representation Learning. - Yihao Xue; Eric Gan; Jiayi Ni; Siddharth Joshi 004; Baharan Mirzasoleiman (ICLR, 2024)

Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization. - Dang Nguyen; Paymon Haddad; Eric Gan; Baharan Mirzasoleiman (NeurIPS, 2024)

Make the Most of Your Data: Changing the Training Data Distribution to Improve In-distribution Generalization Performance. - Dang Nguyen; Paymon Haddad; Eric Gan; Baharan Mirzasoleiman (CoRR, 2024)

Seeing Is Believing: Brain-Inspired Modular Training for Mechanistic Interpretability. - Ziming Liu; Eric Gan; Max Tegmark (Entropy, 2024)