| 2024 | On Convergence of Federated Averaging Langevin Dynamics. | Wei Deng, Qian Zhang, Yian Ma, Zhao Song, Guang Lin |
| 2024 | Reflected Schrdinger Bridge for Constrained Generative Modeling. | Wei Deng, Yu Chen, Nicole Tianjiao Yang, Hengrong Du, Qi Feng, Ricky Tian Qi Chen |
| 2024 | Discrete Probabilistic Inference as Control in Multi-path Environments. | Tristan Deleu, Padideh Nouri, Nikolay Malkin, Doina Precup, Yoshua Bengio |
| 2024 | The Real Deal Behind the Artificial Appeal: Inferential Utility of Tabular Synthetic Data. | Alexander Decruyenaere, Heidelinde Dehaene, Paloma Rabaey, Christiaan Polet, Johan Decruyenaere, Stijn Vansteelandt, Thomas Demeester |
| 2024 | Can we Defend Against the Unknown? An Empirical Study About Threshold Selection for Neural Network Monitoring. | Khoi Tran Dang, Kevin Delmas, Jrmie Guiochet, Joris Gurin |
| 2024 | Power Mean Estimation in Stochastic Monte-Carlo Tree Search. | Tuan Dam, Odalric-Ambrym Maillard, Emilie Kaufmann |
| 2024 | Linear Opinion Pooling for Uncertainty Quantification on Graphs. | Clemens Damke, Eyke Hllermeier |
| 2024 | Normalizing Flows for Conformal Regression. | Nicol Colombo |
| 2024 | Towards Representation Learning for Weighting Problems in Design-Based Causal Inference. | Oscar Clivio, Avi Feller, Chris C. Holmes |
| 2024 | Towards Minimax Optimality of Model-based Robust Reinforcement Learning. | Pierre Clavier, Erwan Le Pennec, Matthieu Geist |
| 2024 | Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression. | Lucas Clart, Adrien Vandenbroucque, Guillaume Dalle, Bruno Loureiro, Florent Krzakala, Lenka Zdeborov |
| 2024 | Fast Interactive Search under a Scale-Free Comparison Oracle. | Daniyar Chumbalov, Lars Klein, Lucas Maystre, Matthias Grossglauser |
| 2024 | Differentiable Pareto-Smoothed Weighting for High-Dimensional Heterogeneous Treatment Effect Estimation. | Yoichi Chikahara, Kansei Ushiyama |
| 2024 | End-to-end Conditional Robust Optimization. | Abhilash Reddy Chenreddy, Erick Delage |
| 2024 | Conditional Bayesian Quadrature. | Zonghao Chen, Masha Naslidnyk, Arthur Gretton, Franois-Xavier Briol |
| 2024 | Adaptive Time-Stepping Schedules for Diffusion Models. | Yuzhu Chen, Fengxiang He, Shi Fu, Xinmei Tian, Dacheng Tao |
| 2024 | Inference for Optimal Linear Treatment Regimes in Personalized Decision-making. | Yuwen Cheng, Shu Yang |
| 2024 | SMuCo: Reinforcement Learning for Visual Control via Sequential Multi-view Total Correlation. | Tong Cheng, Hang Dong, Lu Wang, Bo Qiao, Qingwei Lin, Saravan Rajmohan, Thomas Moscibroda |
| 2024 | Gradient descent in matrix factorization: Understanding large initialization. | Hengchao Chen, Xin Chen, Mohamad Elmasri, Qiang Sun |
| 2024 | Generalization and Learnability in Multiple Instance Regression. | Kushal Chauhan, Rishi Saket, Lorne Applebaum, Ashwinkumar Badanidiyuru, Chandan Giri, Aravindan Raghuveer |
| 2024 | QuantProb: Generalizing Probabilities along with Predictions for a Pre-trained Classifier. | Aditya Challa, Soma S. Dhavala, Snehanshu Saha |
| 2024 | How to Fix a Broken Confidence Estimator: Evaluating Post-hoc Methods for Selective Classification with Deep Neural Networks. | Lus Felipe P. Cattelan, Danilo Silva |
| 2024 | Multi-Relational Structural Entropy. | Yuwei Cao, Hao Peng, Angsheng Li, Chenyu You, Zhifeng Hao, Philip S. Yu |
| 2024 | Fair Active Learning in Low-Data Regimes. | Romain Camilleri, Andrew Wagenmaker, Jamie Morgenstern, Lalit Jain, Kevin Jamieson |
| 2024 | Privacy-Aware Randomized Quantization via Linear Programming. | Zhongteng Cai, Xueru Zhang, Mohammad Mahdi Khalili |