Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning

7 July 2023

Papers citing "Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning"

10 / 10 papers shown

Title
Mastering Atari with Discrete World Models Danijar Hafner Timothy Lillicrap Mohammad Norouzi Jimmy Ba DRL 81 834 0 05 Oct 2020
Phasic Policy Gradient K. Cobbe Jacob Hilton Oleg Klimov John Schulman OffRL 37 155 0 09 Sep 2020
Object-Centric Learning with Slot Attention Francesco Locatello Dirk Weissenborn Thomas Unterthiner Aravindh Mahendran G. Heigold Jakob Uszkoreit Alexey Dosovitskiy Thomas Kipf OCL 185 832 0 26 Jun 2020
Deep Reinforcement and InfoMax Learning Bogdan Mazoure Rémi Tachet des Combes T. Doan Philip Bachman R. Devon Hjelm AI4CE 58 109 0 12 Jun 2020
Primal Wasserstein Imitation Learning Robert Dadashi Léonard Hussenot Matthieu Geist Olivier Pietquin 35 124 0 08 Jun 2020
Causal Induction from Visual Observations for Goal Directed Tasks Sunjay Cauligi Yuke Zhu D. Stefan Tamara Rezk CML LRM 54 63 0 03 Oct 2019
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures L. Espeholt Hubert Soyer Rémi Munos Karen Simonyan Volodymyr Mnih ... Vlad Firoiu Tim Harley Iain Dunning Shane Legg Koray Kavukcuoglu 149 1,584 0 05 Feb 2018
Proximal Policy Optimization Algorithms John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov OffRL 243 18,685 0 20 Jul 2017
Layer Normalization Jimmy Lei Ba J. Kiros Geoffrey E. Hinton 285 10,412 0 21 Jul 2016
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks Andrew M. Saxe James L. McClelland Surya Ganguli ODL 130 1,830 0 20 Dec 2013