Papers
938 papers found
Subspace Inference for Bayesian Deep Learning
Pavel Izmailov, Wesley J. Maddox, Polina Kirichenko et al.
The 35th Uncertainty in Artificial Intelligence Conference: Preface
Ryan Adams, Vibhav Gogate
The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA
Luigi Gresele, Paul K. Rubenstein, Arash Mehrjou et al.
The Role of Memory in Stochastic Optimization
Antonio Orvieto, Jonas Kohler, Aurelien Lucchi
The Sensitivity of Counterfactual Fairness to Unmeasured Confounding
Niki Kilbertus, Philip J. Ball, Matt J. Kusner et al.
Towards a Better Understanding and Regularization of GAN Training Dynamics
Weili Nie, Ankit B. Patel
Towards Robust Relational Causal Discovery
Sanghack Lee, Vasant Honavar
Truly Proximal Policy Optimization
Yuhui Wang, Hao He, Xiaoyang Tan
Variational Inference of Penalized Regression with Submodular Functions
Koh Takeuchi, Yuichi Yoshida, Yoshinobu Kawahara
Variational Regret Bounds for Reinforcement Learning
Ronald Ortner, Pratik Gajane, Peter Auer
Variational Sparse Coding
Francesco Tonolini, Bjørn Sand Jensen, Roderick Murray-Smith
Variational Training for Large-Scale Noisy-OR Bayesian Networks
Geng Ji, Dehua Cheng, Huazhong Ning et al.
Wasserstein Fair Classification
Ray Jiang, Aldo Pacchiano, Tom Stepleton et al.