| 2025 | Flexible and Efficient Probabilistic PDE Solvers through Gaussian Markov Random Fields. | Tim Weiland, Marvin Pfrtner, Philipp Hennig |
| 2025 | Learning Pareto manifolds in high dimensions: How can regularization help? | Tobias Wegel, Filip Kovacevic, Alexandru Tifrea, Fanny Yang |
| 2025 | Hyperboloid GPLVM for Discovering Continuous Hierarchies via Nonparametric Estimation. | Koshi Watanabe, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama |
| 2025 | Advancing Fairness in Precision Medicine: A Universal Framework for Optimal Treatment Estimation in Censored Data. | Hongni Wang, Junxi Zhang, Na Li, Linglong Kong, Bei Jiang, Xiaodong Yan |
| 2025 | Variance-Dependent Regret Bounds for Nonstationary Linear Bandits. | Zhiyong Wang, Jize Xie, Yi Chen, John C. S. Lui, Dongruo Zhou |
| 2025 | Optimizing Neural Network Training and Quantization with Rooted Logistic Objectives. | Zhu Wang, Praveen Raj Veluswami, Harsh Mishra, Sathya N. Ravi |
| 2025 | RetroDiff: Retrosynthesis as Multi-stage Distribution Interpolation. | Yiming Wang, Yuxuan Song, Yiqun Wang, Minkai Xu, Rui Wang, Hao Zhou, Wei-Ying Ma |
| 2025 | Statistical Learning of Distributionally Robust Stochastic Control in Continuous State Spaces. | Shengbo Wang, Nian Si, Jose H. Blanchet, Zhengyuan Zhou |
| 2025 | Conformal Prediction Under Generalized Covariate Shift with Posterior Drift. | Baozhen Wang, Xingye Qiao |
| 2025 | Empirical Error Estimates for Graph Sparsification. | Siyao Wang, Miles E. Lopes |
| 2025 | Prior-Fitted Networks Scale to Larger Datasets When Treated as Weak Learners. | Yuxin Wang, Botian Jiang, Yiran Guo, Quan Gan, David Wipf, Xuanjing Huang, Xipeng Qiu |
| 2025 | Towards Fair Graph Learning without Demographic Information. | Zichong Wang, Nhat Hoang, Xingyu Zhang, Kevin Bello, Xiangliang Zhang, Sundararaja Sitharama Iyengar, Wenbin Zhang |
| 2025 | On Subjective Uncertainty Quantification and Calibration in Natural Language Generation. | Ziyu Wang, Christopher C. Holmes |
| 2025 | SteinDreamer: Variance Reduction for Text-to-3D Score Distillation via Stein Identity. | Peihao Wang, Zhiwen Fan, Dejia Xu, Dilin Wang, Sreyas Mohan, Forrest N. Iandola, Rakesh Ranjan, Yilei Li, Qiang Liu, Zhangyang Wang, Vikas Chandra |
| 2025 | Reinforcement Learning for Adaptive MCMC. | Congye Wang, Wilson Ye Chen, Heishiro Kanagawa, Chris J. Oates |
| 2025 | Explaining ViTs Using Information Flow. | Chase Walker, Md Rubel Ahmed, Sumit Kumar Jha, Rickard Ewetz |
| 2025 | TRADE: Transfer of Distributions between External Conditions with Normalizing Flows. | Stefan Wahl, Armand Rousselot, Felix Draxler, Ullrich Kthe |
| 2025 | Separation-Based Distance Measures for Causal Graphs. | Jonas Wahl, Jakob Runge |
| 2025 | Task-Driven Discrete Representation Learning. | Long Tung Vuong |
| 2025 | Signal Recovery from Random Dot-Product Graphs under Local Differential Privacy. | Siddharth Vishwanath, Jonathan Hehir |
| 2025 | Steinmetz Neural Networks for Complex-Valued Data. | Shyam Venkatasubramanian, Ali Pezeshki, Vahid Tarokh |
| 2025 | I-trustworthy Models. A framework for trustworthiness evaluation of probabilistic classifiers. | Ritwik Vashistha, Arya Farahi |
| 2025 | Black-Box Uniform Stability for Non-Euclidean Empirical Risk Minimization. | Simon Vary, David Martnez-Rubio, Patrick Rebeschini |
| 2025 | MODL: Multilearner Online Deep Learning. | Antonios Valkanas, Boris N. Oreshkin, Mark Coates |
| 2025 | Sampling From Multiscale Densities With Delayed Rejection Generalized Hamiltonian Monte Carlo. | Gilad Turok, Chirag Modi, Bob Carpenter |