Ensemble Dynamics Models
Ensemble Dynamics Models is a model-based reinforcement learning approach that comprises a collection of multiple probabilistic dynamics models, distinguished by its use of ensemble averaging and uncertainty estimation to improve robustness and generalization in learning system transition dynamics.
22
Publications
862
Citations
92
Authors
41
Institutions
Publications per year
2017–2026
9
Parents
22
Waveguide for Bose-Einstein condensates
Kai Bongs, Sven Burger, S. Dettmer et al. · Physical Review A · 2001 · 176 citations · Full text
The emergence of synchrony in networks of mutually inferring neurons
Ensor Rafael Palacios, Takuya Isomura, Thomas Parr et al. · Scientific Reports · 2019 · 62 citations · Full text
Life Sciences, Biology, Neuroscience +17
1–5 of 22
92
Wellcome Centre for Human Neuroimaging, United Kingdom
1 publications · 62 citations
1
h-index
1
h-index
1
h-index
1
h-index
1
h-index
1–5 of 92
41
Stanford University
Stanford, United States
2 h-index
4 publications
329 citations
National Hospital for Neurology and Neurosurgery
London, United Kingdom
1 h-index
3 publications
186 citations

Université Toulouse III - Paul Sabatier
Toulouse, France
1 h-index
9 publications
351 citations
Systems Dynamics (United States)
Huntsville, United States
1 h-index
1 publications
25 citations
InSightec (Israel)
Tirat Carmel, Israel
1 h-index
1 publications
13 citations
Meta (Israel)
Tel Aviv, Israel
1 h-index
2 publications
34 citations
Purdue University West Lafayette
West Lafayette, United States
1 h-index
2 publications
78 citations
Southern Methodist University
Dallas, United States
1 h-index
2 publications
24 citations
1–8 of 41
2 publications · 130 citations
2
h-index
Repository · 1 publications · 17 citations
1
h-index
PRA · 1 publications · 176 citations
1
h-index
NJP · 1 publications · 13 citations
1
h-index
PRE · 1 publications · 13 citations
1
h-index
1–5