Quantifying Multimodality in World Models

14 December 2021

Papers citing "Quantifying Multimodality in World Models"

8 / 8 papers shown

Title
Policy Entropy for Out-of-Distribution Classification Andreas Sedlmeier Robert Muller Steffen Illium Claudia Linnhoff-Popien OODD OffRL 31 14 0 25 May 2020
Uncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning Andreas Sedlmeier Thomas Gabor Thomy Phan Lenz Belzner Claudia Linnhoff-Popien 23 25 0 31 Dec 2019
Leveraging Procedural Generation to Benchmark Reinforcement Learning K. Cobbe Christopher Hesse Jacob Hilton John Schulman 52 549 0 03 Dec 2019
Overcoming Limitations of Mixture Density Networks: A Sampling and Fitting Framework for Multimodal Future Prediction Osama Makansi Eddy Ilg Özgün Çiçek Thomas Brox 78 191 0 09 Jun 2019
Randomized Prior Functions for Deep Reinforcement Learning Ian Osband John Aslanides Albin Cassirer UQCV BDL 38 375 0 08 Jun 2018
World Models David R Ha Jürgen Schmidhuber SyDa 88 1,050 0 27 Mar 2018
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 236 4,667 0 15 Mar 2017
Concrete Problems in AI Safety Dario Amodei C. Olah Jacob Steinhardt Paul Christiano John Schulman Dandelion Mané 141 2,349 0 21 Jun 2016