| 2022 | Reframed GES with a neural conditional dependence measure. | Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen |
| 2022 | Predictive Whittle networks for time series. | Zhongjie Yu, Fabrizio Ventola, Nils Thoma, Devendra Singh Dhami, Martin Mundt, Kristian Kersting |
| 2022 | Combinatorial Bayesian optimization with random mapping functions to convex polytopes. | Jungtaek Kim, Seungjin Choi, Minsu Cho |
| 2021 | Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling. | Difan Zou, Pan Xu, Quanquan Gu |
| 2021 | Task similarity aware meta learning: theory-inspired improvement on MAML. | Pan Zhou, Yingtian Zou, Xiao-Tong Yuan, Jiashi Feng, Caiming Xiong, Steven C. H. Hoi |
| 2021 | Unsupervised program synthesis for images by sampling without replacement. | Chenghui Zhou, Chun-Liang Li, Barnabs Pczos |
| 2021 | Diagnostics for conditional density models and Bayesian inference algorithms. | David Zhao, Niccol Dalmasso, Rafael Izbicki, Ann B. Lee |
| 2021 | Structured sparsification with joint optimization of group convolution and channel shuffle. | Xin-Yu Zhang, Kai Zhao, Taihong Xiao, Ming-Ming Cheng, Ming-Hsuan Yang |
| 2021 | The complexity of nonconvex-strongly-concave minimax optimization. | Siqi Zhang, Junchi Yang, Cristbal Guzmn, Negar Kiyavash, Niao He |
| 2021 | Enabling long-range exploration in minimization of multimodal functions. | Jiaxin Zhang, Hoang Tran, Dan Lu, Guannan Zhang |
| 2021 | On the distributional properties of adaptive gradients. | Zhiyi Zhang, Ziyin Liu |
| 2021 | Dynamic visualization for L1 fusion convex clustering in near-linear time. | Bingyuan Zhang, Jie Chen, Yoshikazu Terada |
| 2021 | NP-DRAW: A Non-Parametric Structured Latent Variable Model for Image Generation. | Xiaohui Zeng, Raquel Urtasun, Richard S. Zemel, Sanja Fidler, Renjie Liao |
| 2021 | A decentralized policy gradient approach to multi-task reinforcement learning. | Sihan Zeng, Malik Aqeel Anwar, Thinh T. Doan, Arijit Raychowdhury, Justin Romberg |
| 2021 | PROVIDE: a probabilistic framework for unsupervised video decomposition. | Polina Zablotskaia, Edoardo A. Dominici, Leonid Sigal, Andreas M. Lehrmann |
| 2021 | Leveraging probabilistic circuits for nonparametric multi-output regression. | Zhongjie Yu, Mingye Zhu, Martin Trapp, Arseny Skryagin, Kristian Kersting |
| 2021 | Multi-output Gaussian Processes for uncertainty-aware recommender systems. | Yinchong Yang, Florian Buettner |
| 2021 | Explaining fast improvement in online imitation learning. | Xinyan Yan, Byron Boots, Ching-An Cheng |
| 2021 | Robust reinforcement learning under minimax regret for green security. | Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe |
| 2021 | Simple combinatorial algorithms for combinatorial bandits: corruptions and approximations. | Haike Xu, Jian Li |
| 2021 | Preface and Frontmatter. | |
| 2021 | Extendability of causal graphical models: Algorithms and computational complexity. | Marcel Wienbst, Max Bannach, Maciej Liskiewicz |
| 2021 | Certification of iterative predictions in Bayesian neural networks. | Matthew Wicker, Luca Laurenti, Andrea Patane, Nicola Paoletti, Alessandro Abate, Marta Kwiatkowska |
| 2021 | Exploring the loss landscape in neural architecture search. | Colin White, Sam Nolen, Yash Savani |
| 2021 | Finite-time theory for momentum Q-learning. | Bowen Weng, Huaqing Xiong, Lin Zhao, Yingbin Liang, Wei Zhang |