| 2022 | Do Bayesian variational autoencoders know what they don't know? | Misha Glazunov, Apostolis Zarras |
| 2022 | Neural-progressive hedging: Enforcing constraints in reinforcement learning with stochastic programming. | Supriyo Ghosh, Laura Wynter, Shiau Hong Lim, Duc Thien Nguyen |
| 2022 | Mitigating statistical bias within differentially private synthetic data. | Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes |
| 2022 | Estimating transfer entropy under long ranged dependencies. | Sahil Garg, Umang Gupta, Yu Chen, Syamantak Datta Gupta, Yeshaya Adler, Anderson Schneider, Yuriy Nevmyvaka |
| 2022 | Sequential algorithmic modification with test data reuse. | Jean Feng, Gene Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio, Alexej Gossmann |
| 2022 | Self-distribution distillation: efficient uncertainty estimation. | Yassir Fathullah, Mark J. F. Gales |
| 2022 | Implicit kernel meta-learning using kernel integral forms. | John Isak Texas Falk, Carlo Ciliberto, Massimiliano Pontil |
| 2022 | Temporal abstractions-augmented temporally contrastive learning: An alternative to the Laplacian in RL. | Akram Erraqabi, Marlos C. Machado, Mingde Zhao, Sainbayar Sukhbaatar, Alessandro Lazaric, Ludovic Denoyer, Yoshua Bengio |
| 2022 | SENTINEL: taming uncertainty with ensemble based distributional reinforcement learning. | Hannes Eriksson, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis |
| 2022 | Learning explainable templated graphical models. | Varun Embar, Sriram Srinivasan, Lise Getoor |
| 2022 | ResIST: Layer-wise decomposition of ResNets for distributed training. | Chen Dun, Cameron R. Wolfe, Christopher M. Jermaine, Anastasios Kyrillidis |
| 2022 | Improving sign-random-projection via count sketch. | Punit Pankaj Dubey, Bhisham Dev Verma, Rameshwar Pratap, Keegan Kang |
| 2022 | X-MEN: guaranteed XOR-maximum entropy constrained inverse reinforcement learning. | Fan Ding, Yexiang Xue |
| 2022 | Revisiting DP-Means: fast scalable algorithms via parallelism and delayed cluster creation. | Or Dinari, Oren Freifeld |
| 2022 | Variational- and metric-based deep latent space for out-of-distribution detection. | Or Dinari, Oren Freifeld |
| 2022 | Balancing adaptability and non-exploitability in repeated games. | Anthony DiGiovanni, Ambuj Tewari |
| 2022 | Multiclass classification for Hawkes processes. | Christophe Denis, Charlotte Dion-Blanc, Laure Sansonnet |
| 2022 | Bayesian spillover graphs for dynamic networks. | Grace Deng, David S. Matteson |
| 2022 | Bayesian structure learning with generative flow networks. | Tristan Deleu, Antnio Gis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio |
| 2022 | Multi-objective Bayesian optimization over high-dimensional search spaces. | Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy |
| 2022 | Individual fairness in feature-based pricing for monopoly markets. | Shantanu Das, Swapnil Dhamal, Ganesh Ghalme, Shweta Jain, Sujit Gujar |
| 2022 | Faster non-convex federated learning via global and local momentum. | Rudrajit Das, Anish Acharya, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu |
| 2022 | On provably robust meta-Bayesian optimization. | Zhongxiang Dai, Yizhou Chen, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet |
| 2022 | Variational message passing neural network for Maximum-A-Posteriori (MAP) inference. | Zijun Cui, Hanjing Wang, Tian Gao, Kartik Talamadupula, Qiang Ji |
| 2022 | Greedy equivalence search in the presence of latent confounders. | Tom Claassen, Ioan Gabriel Bucur |