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2206.08353
Cited By
Towards Understanding How Machines Can Learn Causal Overhypotheses
16 June 2022
Eliza Kosoy
David M. Chan
Adrian Liu
Jasmine Collins
Bryanna Kaufmann
Sandy Han Huang
Jessica B. Hamrick
John F. Canny
Nan Rosemary Ke
Alison Gopnik
CML
AI4CE
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Papers citing
"Towards Understanding How Machines Can Learn Causal Overhypotheses"
20 / 20 papers shown
Title
CogLM: Tracking Cognitive Development of Large Language Models
Xinglin Wang
Peiwen Yuan
Shaoxiong Feng
Yiwei Li
Boyuan Pan
Heda Wang
Yao Hu
Kan Li
ELM
138
1
0
17 Aug 2024
Teaching Models to Express Their Uncertainty in Words
Stephanie C. Lin
Jacob Hilton
Owain Evans
OOD
96
425
0
28 May 2022
PaLM: Scaling Language Modeling with Pathways
Aakanksha Chowdhery
Sharan Narang
Jacob Devlin
Maarten Bosma
Gaurav Mishra
...
Kathy Meier-Hellstern
Douglas Eck
J. Dean
Slav Petrov
Noah Fiedel
PILM
LRM
537
6,301
0
05 Apr 2022
Training Compute-Optimal Large Language Models
Jordan Hoffmann
Sebastian Borgeaud
A. Mensch
Elena Buchatskaya
Trevor Cai
...
Karen Simonyan
Erich Elsen
Jack W. Rae
Oriol Vinyals
Laurent Sifre
AI4TS
211
1,988
0
29 Mar 2022
Learning Causal Overhypotheses through Exploration in Children and Computational Models
Eliza Kosoy
Adrian Liu
Jasmine Collins
David M. Chan
Jessica B. Hamrick
Nan Rosemary Ke
Sandy H Huang
Bryanna Kaufmann
John F. Canny
Alison Gopnik
CML
58
9
0
21 Feb 2022
A Survey of Exploration Methods in Reinforcement Learning
Susan Amin
Maziar Gomrokchi
Harsh Satija
H. V. Hoof
Doina Precup
OffRL
93
84
0
01 Sep 2021
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning
Nan Rosemary Ke
Aniket Didolkar
Sarthak Mittal
Anirudh Goyal
Guillaume Lajoie
Stefan Bauer
Danilo Jimenez Rezende
Yoshua Bengio
Michael C. Mozer
C. Pal
CML
83
57
0
02 Jul 2021
ACRE: Abstract Causal REasoning Beyond Covariation
Chi Zhang
Baoxiong Jia
Mark Edmonds
Song-Chun Zhu
Yixin Zhu
CML
127
48
0
26 Mar 2021
Neural Production Systems: Learning Rule-Governed Visual Dynamics
Anirudh Goyal
Aniket Didolkar
Nan Rosemary Ke
Charles Blundell
Philippe Beaudoin
N. Heess
Michael C. Mozer
Yoshua Bengio
OCL
108
86
0
02 Mar 2021
Towards Causal Representation Learning
Bernhard Schölkopf
Francesco Locatello
Stefan Bauer
Nan Rosemary Ke
Nal Kalchbrenner
Anirudh Goyal
Yoshua Bengio
OOD
CML
AI4CE
146
322
0
22 Feb 2021
Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning
Sumedh Anand Sontakke
Arash Mehrjou
Laurent Itti
Bernhard Schölkopf
CML
90
63
0
07 Oct 2020
RLBench: The Robot Learning Benchmark & Learning Environment
Stephen James
Z. Ma
David Rovick Arrojo
Andrew J. Davison
SSL
VLM
OffRL
120
563
0
26 Sep 2019
PHYRE: A New Benchmark for Physical Reasoning
A. Bakhtin
Laurens van der Maaten
Justin Johnson
Laura Gustafson
Ross B. Girshick
LRM
71
129
0
15 Aug 2019
Rapid trial-and-error learning with simulation supports flexible tool use and physical reasoning
Kelsey R. Allen
Kevin A. Smith
J. Tenenbaum
LRM
92
118
0
22 Jul 2019
Self-Supervised Exploration via Disagreement
Deepak Pathak
Dhiraj Gandhi
Abhinav Gupta
SSL
85
384
0
10 Jun 2019
BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning
Maxime Chevalier-Boisvert
Dzmitry Bahdanau
Salem Lahlou
Lucas Willems
Chitwan Saharia
Thien Huu Nguyen
Yoshua Bengio
ELM
110
241
0
18 Oct 2018
Count-Based Exploration in Feature Space for Reinforcement Learning
Jarryd Martin
S. N. Sasikumar
Tom Everitt
Marcus Hutter
76
124
0
25 Jun 2017
Curiosity-driven Exploration by Self-supervised Prediction
Deepak Pathak
Pulkit Agrawal
Alexei A. Efros
Trevor Darrell
LRM
SSL
130
2,453
0
15 May 2017
Unifying Count-Based Exploration and Intrinsic Motivation
Marc G. Bellemare
S. Srinivasan
Georg Ostrovski
Tom Schaul
D. Saxton
Rémi Munos
189
1,485
0
06 Jun 2016
Asynchronous Methods for Deep Reinforcement Learning
Volodymyr Mnih
Adria Puigdomenech Badia
M. Berk Mirza
Alex Graves
Timothy Lillicrap
Tim Harley
David Silver
Koray Kavukcuoglu
210
8,882
0
04 Feb 2016
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