Generic 3D Representation via Pose Estimation and Matching. - Amir R. Zamir; Tilman Wekel; Pulkit Agrawal 001; Colin Wei; Jitendra Malik; Silvio Savarese (ECCV (3), 2016)

General Bounds on Satisfiability Thresholds for Random CSPs via Fourier Analysis. - Colin Wei; Stefano Ermon (AAAI, 2017)

Markov Chain Truncation for Doubly-Intractable Inference. - Colin Wei; Iain Murray 001 (AISTATS, 2017)

On the Margin Theory of Feedforward Neural Networks. - Colin Wei; Jason D. Lee; Qiang Liu 001; Tengyu Ma 001 (CoRR, 2018)

Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss. - Kaidi Cao; Colin Wei; Adrien Gaidon; Nikos Aréchiga; Tengyu Ma 001 (NeurIPS, 2019)

Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks. - Yuanzhi Li; Colin Wei; Tengyu Ma 001 (NeurIPS, 2019)

Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel. - Colin Wei; Jason D. Lee; Qiang Liu 001; Tengyu Ma 001 (NeurIPS, 2019)

Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation. - Colin Wei; Tengyu Ma 001 (NeurIPS, 2019)

Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin. - Colin Wei; Tengyu Ma 001 (CoRR, 2019)

Improved Sample Complexities for Deep Neural Networks and Robust Classification via an All-Layer Margin. - Colin Wei; Tengyu Ma 001 (ICLR, 2020)

The Implicit and Explicit Regularization Effects of Dropout. - Colin Wei; Sham M. Kakade; Tengyu Ma 001 (ICML, 2020)

Self-training Avoids Using Spurious Features Under Domain Shift. - Yining Chen; Colin Wei; Ananya Kumar; Tengyu Ma 001 (NeurIPS, 2020)

Meta-learning Transferable Representations with a Single Target Domain. - Hong Liu; Jeff Z. HaoChen; Colin Wei; Tengyu Ma 001 (CoRR, 2020)

Shape Matters: Understanding the Implicit Bias of the Noise Covariance. - Jeff Z. HaoChen; Colin Wei; Jason D. Lee; Tengyu Ma 001 (COLT, 2021)

Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data. - Colin Wei; Kendrick Shen; Yining Chen; Tengyu Ma 001 (ICLR, 2021)

Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss. - Jeff Z. HaoChen; Colin Wei; Adrien Gaidon; Tengyu Ma 001 (NeurIPS, 2021)

Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning. - Colin Wei; Sang Michael Xie; Tengyu Ma 001 (NeurIPS, 2021)

Certified Robustness for Deep Equilibrium Models via Interval Bound Propagation. - Colin Wei; J. Zico Kolter (ICLR, 2022)

Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations. - Jeff Z. HaoChen; Colin Wei; Ananya Kumar; Tengyu Ma 001 (NeurIPS, 2022)

Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers. - Colin Wei; Yining Chen; Tengyu Ma 001 (NeurIPS, 2022)

Theoretical insights on generalization in supervised and self-supervised deep learning. - Colin Wei (2022)

Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence. - Margalit Glasgow; Colin Wei; Mary Wootters; Tengyu Ma 001 (ICLR, 2023)

GPT-4o System Card. - Aaron Hurst; Adam Lerer; Adam P. Goucher; Adam Perelman; Aditya Ramesh; Aidan Clark; AJ Ostrow; Akila Welihinda; Alan Hayes; Alec Radford; Aleksander Madry; Alex Baker-Whitcomb; et al. (CoRR, 2024)