| 2024 | Sample Average Approximation for Black-Box Variational Inference. | Javier Burroni, Justin Domke, Daniel Sheldon |
| 2024 | Revisiting Kernel Attention with Correlated Gaussian Process Representation. | Long Minh Bui, Tho Tran Huu, Duy Dinh, Tan Minh Nguyen, Trong Nghia Hoang |
| 2024 | Products, Abstractions and Inclusions of Causal Spaces. | Simon Buchholz, Junhyung Park, Bernhard Schlkopf |
| 2024 | Polynomial Semantics of Tractable Probabilistic Circuits. | Oliver Broadrick, Honghua Zhang, Guy Van den Broeck |
| 2024 | Using Autodiff to Estimate Posterior Moments, Marginals and Samples. | Sam Bowyer, Thomas Heap, Laurence Aitchison |
| 2024 | DistriBlock: Identifying adversarial audio samples by leveraging characteristics of the output distribution. | Matas P. Pizarro B., Dorothea Kolossa, Asja Fischer |
| 2024 | Publishing Number of Walks and Katz Centrality under Local Differential Privacy. | Louis Betzer, Vorapong Suppakitpaisarn, Quentin Hillebrand |
| 2024 | Shedding Light on Large Generative Networks: Estimating Epistemic Uncertainty in Diffusion Models. | Lucas Berry, Axel Brando, David Meger |
| 2024 | MetaCOG: A Heirarchical Probabilistic Model for Learning Meta-Cognitive Visual Representations. | Marlene Berke, Zhangir Azerbayev, Mario Belledonne, Zenna Tavares, Julian Jara-Ettinger |
| 2024 | Linearly Constrained Gaussian Processes are SkewGPs: application to Monotonic Preference Learning and Desirability. | Alessio Benavoli, Dario Azzimonti |
| 2024 | Towards Bounding Causal Effects under Markov Equivalence. | Alexis Bellot |
| 2024 | Detecting critical treatment effect bias in small subgroups. | Piersilvio De Bartolomeis, Javier Abad, Konstantin Donhauser, Fanny Yang |
| 2024 | Learning Accurate and Interpretable Decision Trees. | Maria-Florina Balcan, Dravyansh Sharma |
| 2024 | Walking the Values in Bayesian Inverse Reinforcement Learning. | Ondrej Bajgar, Alessandro Abate, Konstantinos Gatsis, Michael A. Osborne |
| 2024 | Differentially Private No-regret Exploration in Adversarial Markov Decision Processes. | Shaojie Bai, Lanting Zeng, Chengcheng Zhao, Xiaoming Duan, Mohammad Sadegh Talebi, Peng Cheng, Jiming Chen |
| 2024 | Inference in Probabilistic Answer Set Programs with Imprecise Probabilities via Optimization. | Damiano Azzolini, Fabrizio Riguzzi |
| 2024 | Mitigating Overconfidence in Out-of-Distribution Detection by Capturing Extreme Activations. | Mohammad Azizmalayeri, Ameen Abu-Hanna, Giovanni Cin |
| 2024 | On the Capacitated Facility Location Problem with Scarce Resources. | Gennaro Auricchio, Harry J. Clough, Jie Zhang |
| 2024 | Identifiability of total effects from abstractions of time series causal graphs. | Charles K. Assaad, Emilie Devijver, ric Gaussier, Gregor Goessler, Anouar Meynaoui |
| 2024 | FedAST: Federated Asynchronous Simultaneous Training. | Baris Askin, Pranay Sharma, Carlee Joe-Wong, Gauri Joshi |
| 2024 | Latent Representation Entropy Density for Distribution Shift Detection. | Fabio Arnez, Daniel Alfonso Montoya Vasquez, Ansgar Radermacher, Franois Terrier |
| 2024 | Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling. | Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba |
| 2024 | CSS: Contrastive Semantic Similarities for Uncertainty Quantification of LLMs. | Shuang Ao, Stefan Rueger, Advaith Siddharthan |
| 2024 | Iterated INLA for State and Parameter Estimation in Nonlinear Dynamical Systems. | Rafael Anderka, Marc Peter Deisenroth, So Takao |
| 2024 | Metric Learning from Limited Pairwise Preference Comparisons. | Zhi Wang, Geelon So, Ramya Korlakai Vinayak |