| 2025 | COLT | Mean-field analysis of polynomial-width two-layer neural network beyond finite time horizon. | Margalit Glasgow, Denny Wu, Joan Bruna |
| 2025 | COLT | Learning Compositional Functions with Transformers from Easy-to-Hard Data. | Zixuan Wang, Eshaan Nichani, Alberto Bietti, Alex Damian, Daniel Hsu, Jason D. Lee, Denny Wu |
| 2025 | ICLR | Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics. | Alireza Mousavi-Hosseini, Denny Wu, Murat A. Erdogdu |
| 2025 | ICML | Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and Distillation. | Juno Kim, Denny Wu, Jason D. Lee, Taiji Suzuki |
| 2025 | ICML | Nonlinear transformers can perform inference-time feature learning. | Naoki Nishikawa, Yujin Song, Kazusato Oko, Denny Wu, Taiji Suzuki |
| 2024 | AISTATS | Why is parameter averaging beneficial in SGD? An objective smoothing perspective. | Atsushi Nitanda, Ryuhei Kikuchi, Shugo Maeda, Denny Wu |
| 2024 | COLT | Learning sum of diverse features: computational hardness and efficient gradient-based training for ridge combinations. | Kazusato Oko, Yujin Song, Taiji Suzuki, Denny Wu |
| 2024 | COLT | Nonlinear spiked covariance matrices and signal propagation in deep neural networks. | Zhichao Wang, Denny Wu, Zhou Fan |
| 2024 | ICLR | Improved statistical and computational complexity of the mean-field Langevin dynamics under structured data. | Atsushi Nitanda, Kazusato Oko, Taiji Suzuki, Denny Wu |
| 2024 | ICML | SILVER: Single-loop variance reduction and application to federated learning. | Kazusato Oko, Shunta Akiyama, Denny Wu, Tomoya Murata, Taiji Suzuki |
| 2023 | ICLR | Uniform-in-time propagation of chaos for the mean-field gradient Langevin dynamics. | Taiji Suzuki, Atsushi Nitanda, Denny Wu |
| 2023 | ICML | Primal and Dual Analysis of Entropic Fictitious Play for Finite-sum Problems. | Atsushi Nitanda, Kazusato Oko, Denny Wu, Nobuhito Takenouchi, Taiji Suzuki |
| 2022 | AISTATS | Convex Analysis of the Mean Field Langevin Dynamics. | Atsushi Nitanda, Denny Wu, Taiji Suzuki |
| 2022 | ICLR | Understanding the Variance Collapse of SVGD in High Dimensions. | Jimmy Ba, Murat A. Erdogdu, Marzyeh Ghassemi, Shengyang Sun, Taiji Suzuki, Denny Wu, Tianzong Zhang |
| 2022 | ICLR | Particle Stochastic Dual Coordinate Ascent: Exponential convergent algorithm for mean field neural network optimization. | Kazusato Oko, Taiji Suzuki, Atsushi Nitanda, Denny Wu |
| 2021 | ICLR | When does preconditioning help or hurt generalization? | Shun-ichi Amari, Jimmy Ba, Roger Baker Grosse, Xuechen Li, Atsushi Nitanda, Taiji Suzuki, Denny Wu, Ji Xu |
| 2020 | ICLR | Generalization of Two-layer Neural Networks: An Asymptotic Viewpoint. | Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Denny Wu, Tianzong Zhang |
| 2019 | ICLR | Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator. | Makoto Yamada, Denny Wu, Yao-Hung Hubert Tsai, Hirofumi Ohta, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu |
| 2018 | ICLR | Selecting the Best in GANs Family: a Post Selection Inference Framework. | Yao-Hung Hubert Tsai, Denny Wu, Makoto Yamada, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu |