| 2021 | On the distribution of penultimate activations of classification networks. | Minkyo Seo, Yoonho Lee, Suha Kwak |
| 2021 | Identifying untrustworthy predictions in neural networks by geometric gradient analysis. | Leo Schwinn, An Nguyen, Ren Raab, Leon Bungert, Daniel Tenbrinck, Dario Zanca, Martin Burger, Bjrn M. Eskofier |
| 2021 | Classification with abstention but without disparities. | Nicolas Schreuder, Evgenii Chzhen |
| 2021 | Doubly non-central beta matrix factorization for DNA methylation data. | Aaron Schein, Anjali Nagulpally, Hanna M. Wallach, Patrick Flaherty |
| 2021 | Efficient online inference for nonparametric mixture models. | Rylan Schaeffer, Blake Bordelon, Mikail Khona, Weiwei Pan, Ila Rani Fiete |
| 2021 | Modeling financial uncertainty with multivariate temporal entropy-based curriculums. | Ramit Sawhney, Arnav Wadhwa, Ayush Mangal, Vivek Mittal, Shivam Agarwal, Rajiv Ratn Shah |
| 2021 | Improved generalization bounds of group invariant / equivariant deep networks via quotient feature spaces. | Akiyoshi Sannai, Masaaki Imaizumi, Makoto Kawano |
| 2021 | Hierarchical infinite relational model. | Feras A. Saad, Vikash K. Mansinghka |
| 2021 | The neural moving average model for scalable variational inference of state space models. | Thomas Ryder, Dennis Prangle, Andrew Golightly, Isaac Matthews |
| 2021 | Unbiased gradient estimation for variational auto-encoders using coupled Markov chains. | Francisco J. R. Ruiz, Michalis K. Titsias, A. Taylan Cemgil, Arnaud Doucet |
| 2021 | Compositional abstraction error and a category of causal models. | Eigil Fjeldgren Rischel, Sebastian Weichwald |
| 2021 | Maximal ancestral graph structure learning via exact search. | Kari Rantanen, Antti Hyttinen, Matti Jrvisalo |
| 2021 | Class balancing GAN with a classifier in the loop. | Harsh Rangwani, Konda Reddy Mopuri, R. Venkatesh Babu |
| 2021 | Variance reduction in frequency estimators via control variates method. | Rameshwar Pratap, Raghav Kulkarni |
| 2021 | Competitive policy optimization. | Manish Prajapat, Kamyar Azizzadenesheli, Alexander Liniger, Yisong Yue, Anima Anandkumar |
| 2021 | Distribution-free uncertainty quantification for classification under label shift. | Aleksandr Podkopaev, Aaditya Ramdas |
| 2021 | GP-ConvCNP: Better generalization for conditional convolutional Neural Processes on time series data. | Jens Petersen, Gregor Khler, David Zimmerer, Fabian Isensee, Paul F. Jger, Klaus H. Maier-Hein |
| 2021 | Addressing fairness in classification with a model-agnostic multi-objective algorithm. | Kirtan Padh, Diego Antognini, Emma Lejal Glaude, Boi Faltings, Claudiu Musat |
| 2021 | Towards tractable optimism in model-based reinforcement learning. | Aldo Pacchiano, Philip J. Ball, Jack Parker-Holder, Krzysztof Choromanski, Stephen Roberts |
| 2021 | Uncertainty-aware sensitivity analysis using Rnyi divergences. | Topi Paananen, Michael Riis Andersen, Aki Vehtari |
| 2021 | No-regret approximate inference via Bayesian optimisation. | Rafael Oliveira, Lionel Ott, Fabio Ramos |
| 2021 | Approximation algorithm for submodular maximization under submodular cover. | Naoto Ohsaka, Tatsuya Matsuoka |
| 2021 | Mixed variable Bayesian optimization with frequency modulated kernels. | ChangYong Oh, Efstratios Gavves, Max Welling |
| 2021 | Matrix games with bandit feedback. | Brendan O'Donoghue, Tor Lattimore, Ian Osband |
| 2021 | The promises and pitfalls of deep kernel learning. | Sebastian W. Ober, Carl E. Rasmussen, Mark van der Wilk |