33 citations · 64 across the 9 of their papers we have counts for
4 papers · 1 filter
Bridging the Gap Between Target Networks and Functional Regularization
Alexandre Piche, Valentin Thomas, Joseph Marino +4
Bootstrapping is behind much of the successes of Deep Reinforcement Learning. However, learning the value function via bootstrapping often leads to unstable training due to fast-ch…
Iterative Amortized Policy Optimization
Joseph Marino, Alexandre Piché, Alessandro Davide Ialongo +1
Policy networks are a central feature of deep reinforcement learning (RL) algorithms for continuous control, enabling the estimation and sampling of high-value actions. From the va…
Improving Sequential Latent Variable Models with Autoregressive Flows
Joseph Marino, Lei Chen, Jiawei He +1
We propose an approach for improving sequence modeling based on autoregressive normalizing flows. Each autoregressive transform, acting across time, serves as a moving frame of ref…
Iterative Amortized Inference
Joseph Marino, Yisong Yue, Stephan Mandt
Inference models are a key component in scaling variational inference to deep latent variable models, most notably as encoder networks in variational auto-encoders (VAEs). By repla…