DeepHack.RL: Mikhail Burtsev - Model-based reinforcement learning for alternating environments
DeepHack.Turing: Mikhail Burtsev - iPavlov: Conversational Intelligence Project
Mikhail Burtsev: Deep Pavlov
DeepHack.RL: Gabriel Synnaeve - E2D2: Episodic exploration for deep deterministic policies
DeepHack.RL: Doina Precup - Temporal abstraction in reinforcement learning
DeepHack.RL: Marc Bellemare - The role of density models in reinforcement learning
DeepHack.RL: Andrew Barto - Intrinsically motivated reinforcement learning
DeepHack.RL: Alexey Dosovitskiy - Visuomotor control in 3D environments
DeepHack.RL: Tejas Kulkarni - Revisiting successor representations
Michiel van de Panne - Learning abstractions for sensory motor control
The Deephack and dotChuckles Podcast 1
DeepHack.Q&A Anatoly Levenchuk – Machine learning engineering
RL#9: Model-Based Reinforcement Learning
2018 09 08 Advanced model based RL
RL#1: Exploration in RL
DeepHack.Babel. Maja Popovic. Evaluation of Machine Translation.
Model-based Reinforcement Learning Control for Adaptive Optics
DeepHack.Turing: Maksim Kretov - Applications of RL techniques in NLP: An overview
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models
Model-Based Policy Optimization (ICML Workshops)
