| 2021 | Local explanations via necessity and sufficiency: unifying theory and practice. | David S. Watson, Limor Gultchin, Ankur Taly, Luciano Floridi |
| 2021 | Statistically robust neural network classification. | Benjie Wang, Stefan Webb, Tom Rainforth |
| 2021 | Explicit pairwise factorized graph neural network for semi-supervised node classification. | Yu Wang, Yuesong Shen, Daniel Cremers |
| 2021 | CORe: Capitalizing On Rewards in Bandit Exploration. | Nan Wang, Branislav Kveton, Maryam Karimzadehgan |
| 2021 | Natural language adversarial defense through synonym encoding. | Xiaosen Wang, Jin Hao, Yichen Yang, Kun He |
| 2021 | Post-hoc loss-calibration for Bayesian neural networks. | Meet P. Vadera, Soumya Ghosh, Kenney Ng, Benjamin M. Marlin |
| 2021 | Know your limits: Uncertainty estimation with ReLU classifiers fails at reliable OOD detection. | Dennis Ulmer, Giovanni Cin |
| 2021 | Probabilistic selection of inducing points in sparse Gaussian processes. | Anders Kirk Uhrenholt, Valentin Charvet, Bjrn Sand Jensen |
| 2021 | Bias-corrected peaks-over-threshold estimation of the CVaR. | Dylan Troop, Frdric Godin, Jia Yuan Yu |
| 2021 | Causal and interventional Markov boundaries. | Sofia Triantafillou, Fattaneh Jabbari, Gregory F. Cooper |
| 2021 | Information theoretic meta learning with Gaussian processes. | Michalis K. Titsias, Francisco J. R. Ruiz, Sotirios Nikoloutsopoulos, Alexandre Galashov |
| 2021 | Incorporating causal graphical prior knowledge into predictive modeling via simple data augmentation. | Takeshi Teshima, Masashi Sugiyama |
| 2021 | Bandits with partially observable confounded data. | Guy Tennenholtz, Uri Shalit, Shie Mannor, Yonathan Efroni |
| 2021 | Combining pseudo-point and state space approximations for sum-separable Gaussian Processes. | Will Tebbutt, Arno Solin, Richard E. Turner |
| 2021 | Symmetric Wasserstein autoencoders. | Sun Sun, Hongyu Guo |
| 2021 | Confidence in causal discovery with linear causal models. | David Strieder, Tobias Freidling, Stefan Haffner, Mathias Drton |
| 2021 | Learning proposals for probabilistic programs with inference combinators. | Sam Stites, Heiko Zimmermann, Hao Wu, Eli Sennesh, Jan-Willem van de Meent |
| 2021 | Path dependent structural equation models. | Ranjani Srinivasan, Jaron J. R. Lee, Rohit Bhattacharya, Ilya Shpitser |
| 2021 | Subseasonal climate prediction in the western US using Bayesian spatial models. | Vishwak Srinivasan, Justin Khim, Arindam Banerjee, Pradeep Ravikumar |
| 2021 | PLSO: A generative framework for decomposing nonstationary time-series into piecewise stationary oscillatory components. | Andrew H. Song, Demba E. Ba, Emery N. Brown |
| 2021 | Unsupervised anomaly detection with adversarial mirrored autoencoders. | Gowthami Somepalli, Yexin Wu, Yogesh Balaji, Bhanukiran Vinzamuri, Soheil Feizi |
| 2021 | Invariant representation learning for treatment effect estimation. | Claudia Shi, Victor Veitch, David M. Blei |
| 2021 | Graph-based semi-supervised learning through the lens of safety. | Shreyas Sheshadri, Avirup Saha, Priyank Patel, Samik Datta, Niloy Ganguly |
| 2021 | Sketching curvature for efficient out-of-distribution detection for deep neural networks. | Apoorva Sharma, Navid Azizan, Marco Pavone |
| 2021 | Principal component analysis in the stochastic differential privacy model. | Fanhua Shang, Zhihui Zhang, Tao Xu, Yuanyuan Liu, Hongying Liu |