Neural Relational Inference for Interacting Systems
By Thomas Kipf · Ethan Fetaya · Kuan-Chieh Wang · Max Welling · Richard Zemel


Distilling the Posterior in Bayesian Neural Networks
By Kuan-Chieh Wang · Paul Vicol · James Lucas · Li Gu · Roger Grosse · Richard Zemel


Reviving and Improving Recurrent Back-Propagation
By Renjie Liao · Yuwen Xiong · Ethan Fetaya · Lisa Zhang · KiJung Yoon · Zachary S Pitkow · Raquel Urtasun · Richard Zemel


Learning Adversarially Fair and Transferable Representations
By David Madras · Elliot Creager · Toniann Pitassi · Richard Zemel


Inference Suboptimality in Variational Autoencoders
By Chris Cremer · Xuechen Li · David Duvenaud


Noisy Natural Gradient as Variational Inference
By Guodong Zhang · Shengyang Sun · David Duvenaud · Roger Grosse


Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control
By Yangchen Pan · Amir-massoud Farahmand · Martha White · Saleh Nabi · Piyush Grover · Daniel Nikovski


Differentiable Compositional Kernel Learning for Gaussian Processes
By Shengyang Sun · Guodong Zhang · Chaoqi Wang · Wenyuan Zeng · Jiaman Li · Roger Grosse


Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors
By Gintare Karolina Dziugaite · Daniel Roy


Learning to Reweight Examples for Robust Deep Learning
By Mengye Ren · Wenyuan Zeng · Bin Yang · Raquel Urtasun


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