| 2025 | Adaptive Human-Robot Collaboration using Type-Based IRL. | Prasanth Sengadu Suresh, Prashant Doshi, Bikramjit Banerjee |
| 2025 | On Constant Regret for Low-Rank MDPs. | Alexander Sturm, Sebastian Tschiatschek |
| 2025 | Nonparametric Bayesian inference of item-level features in classifier combination. | Patrick Stinson, Nikolaus Kriegeskorte |
| 2025 | Pure and Strong Nash Equilibrium Computation in Compactly Representable Aggregate Games. | Jared Soundy, Mohammad T. Irfan, Hau Chan |
| 2025 | RDI: An adversarial robustness evaluation metric for deep neural networks based on model statistical features. | Jialei Song, Xingquan Zuo, Feiyang Wang, Hai Huang, Tianle Zhang |
| 2025 | Privacy-Preserving Neural Processes for Probabilistic User Modeling. | Amir Sonee, Haripriya Harikumar, Alex Hmlinen, Lukas Prediger, Samuel Kaski |
| 2025 | Proxy-informed Bayesian transfer learning with unknown sources. | Sabina J. Sloman, Julien Martinelli, Samuel Kaski |
| 2025 | Approximate Bayesian Inference via Bitstring Representations. | Aleksanteri M. Sladek, Martin Trapp, Arno Solin |
| 2025 | Learning from Label Proportions and Covariate-shifted Instances. | Sagalpreet Singh, Navodita Sharma, Shreyas Havaldar, Rishi Saket, Aravindan Raghuveer |
| 2025 | Truthful Elicitation of Imprecise Forecasts. | Anurag Singh, Siu Lun Chau, Krikamol Muandet |
| 2025 | The Causal Information Bottleneck and Optimal Causal Variable Abstractions. | Francisco Nunes Ferreira Quialheiro Simoes, Mehdi Dastani, Thijs van Ommen |
| 2025 | Critical Influence of Overparameterization on Sharpness-aware Minimization. | Sungbin Shin, Dongyeop Lee, Maksym Andriushchenko, Namhoon Lee |
| 2025 | Minimax Optimal Nonsmooth Nonparametric Regression via Fractional Laplacian Eigenmaps. | Zhaoyang Shi, Krishna Balasubramanian, Wolfgang Polonik |
| 2025 | Learning Robust XGBoost Ensembles for Regression Tasks. | Atri Vivek Sharma, Panagiotis Kouvaros, Alessio Lomuscio |
| 2025 | Experimentation under Treatment Dependent Network Interference. | Shiv Shankar, Ritwik Sinha, Madalina Fiterau |
| 2025 | Divide and Orthogonalize: Efficient Continual Learning with Local Model Space Projection. | Jin Shang, Simone Shao, Tian Tong, Fan Yang, Yetian Chen, Yang Jiao, Jia Liu, Yan Gao |
| 2025 | Reparameterizing Hybrid Markov Logic Networks to handle Covariate-Shift in Representations. | Anup Shakya, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal |
| 2025 | Conformal Prediction Sets for Deep Generative Models via Reduction to Conformal Regression. | Hooman Shahrokhi, Devjeet Raj Roy, Yan Yan, Venera Arnaoudova, Jana Doppa |
| 2025 | Scaling Probabilistic Circuits via Data Partitioning. | Jonas Seng, Florian Peter Busch, Pooja Prasad, Devendra Singh Dhami, Martin Mundt, Kristian Kersting |
| 2025 | Revisiting the Equivalence of Bayesian Neural Networks and Gaussian Processes: On the Importance of Learning Activations. | Marcin Sendera, Amin Sorkhei, Tomasz Kusmierczyk |
| 2025 | Distributionally and Adversarially Robust Logistic Regression via Intersecting Wasserstein Balls. | Aras Selvi, Eleonora Kreacic, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso |
| 2025 | On Information-Theoretic Measures of Predictive Uncertainty. | Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Sepp Hochreiter |
| 2025 | Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference. | Colin Samplawski, Adam D. Cobb, Manoj Acharya, Ramneet Kaur, Susmit Jha |
| 2025 | Learning with Confidence. | Oliver E. Richardson |
| 2025 | COS-DPO: Conditioned One-Shot Multi-Objective Fine-Tuning Framework. | Yinuo Ren, Tesi Xiao, Michael Shavlovsky, Lexing Ying, Holakou Rahmanian |