| 2025 | Distance Estimation for High-Dimensional Discrete Distributions. | Kuldeep S. Meel, Gunjan Kumar, Yash Pote |
| 2025 | Variation Due to Regularization Tractably Recovers Bayesian Deep Learning Uncertainty. | James McInerney, Nathan Kallus |
| 2025 | An Adaptive Method for Weak Supervision with Drifting Data. | Alessio Mazzetto, Reza Esfandiarpoor, Akash Singirikonda, Eli Upfal, Stephen H. Bach |
| 2025 | Synthetic Potential Outcomes and Causal Mixture Identifiability. | Bijan Mazaheri, Chandler Squires, Caroline Uhler |
| 2025 | Statistical Test for Auto Feature Engineering by Selective Inference. | Tatsuya Matsukawa, Tomohiro Shiraishi, Shuichi Nishino, Teruyuki Katsuoka, Ichiro Takeuchi |
| 2025 | Recursive Learning of Asymptotic Variational Objectives. | Alessandro Mastrototaro, Mathias Mller, Jimmy Olsson |
| 2025 | Transfer Learning for High-dimensional Reduced Rank Time Series Models. | Mingliang Ma, Abolfazl Safikhani |
| 2025 | On the Computational Tractability of the (Many) Shapley Values. | Reda Marzouk, Shahaf Bassan, Guy Katz, Colin de la Higuera |
| 2025 | Sequential Kernelized Stein Discrepancy. | Diego Martinez-Taboada, Aaditya Ramdas |
| 2025 | Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric Penalties. | David Martnez-Rubio, Christophe Roux, Christopher Criscitiello, Sebastian Pokutta |
| 2025 | Pick-to-Learn and Self-Certified Gaussian Process Approximations. | Daniel Marks, Dario Paccagnan |
| 2025 | Implicit Diffusion: Efficient optimization through stochastic sampling. | Pierre Marion, Anna Korba, Peter L. Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-Lpez, Courtney Paquette, Quentin Berthet |
| 2025 | Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix. | Charles Margossian, Lawrence K. Saul |
| 2025 | All or None: Identifiable Linear Properties of Next-Token Predictors in Language Modeling. | Emanuele Marconato, Sbastien Lachapelle, Sebastian Weichwald, Luigi Gresele |
| 2025 | Refined Analysis of Constant Step Size Federated Averaging and Federated Richardson-Romberg Extrapolation. | Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Sergey Samsonov, Eric Moulines |
| 2025 | Performative Reinforcement Learning with Linear Markov Decision Process. | Debmalya Mandal, Goran Radanovic |
| 2025 | Corruption Robust Offline Reinforcement Learning with Human Feedback. | Debmalya Mandal, Andi Nika, Parameswaran Kamalaruban, Adish Singla, Goran Radanovic |
| 2025 | A Unified Evaluation Framework for Epistemic Predictions. | Shireen Kudukkil Manchingal, Muhammad Mubashar, Kaizheng Wang, Fabio Cuzzolin |
| 2025 | Synthesis and Analysis of Data as Probability Measures With Entropy-Regularized Optimal Transport. | Brendan Mallery, James M. Murphy, Shuchin Aeron |
| 2025 | Hypernym Bias: Unraveling Deep Classifier Training Dynamics through the Lens of Class Hierarchy. | Roman Malashin, Valeria Yachnaya, Alexandr V. Mullin |
| 2025 | Locally Private Estimation with Public Features. | Yuheng Ma, Ke Jia, Hanfang Yang |
| 2025 | On the Consistent Recovery of Joint Distributions from Conditionals. | Mahbod Majid, Rattana Pukdee, Vishwajeet Agrawal, Burak Varici, Pradeep Kumar Ravikumar |
| 2025 | Adversarially-Robust TD Learning with Markovian Data: Finite-Time Rates and Fundamental Limits. | Sreejeet Maity, Aritra Mitra |
| 2025 | posteriordb: Testing, Benchmarking and Developing Bayesian Inference Algorithms. | Mns Magnusson, Jakob Torgander, Paul-Christian Brkner, Lu Zhang, Bob Carpenter, Aki Vehtari |
| 2025 | Tamed Langevin sampling under weaker conditions. | Iosif Lytras, Panayotis Mertikopoulos |