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Disentangling the independently controllable factors of variation by
  interacting with the world

Disentangling the independently controllable factors of variation by interacting with the world

26 February 2018
Valentin Thomas
Emmanuel Bengio
W. Fedus
Jules Pondard
Philippe Beaudoin
Hugo Larochelle
Joelle Pineau
Doina Precup
Yoshua Bengio
    DRL
    CoGe
    CML
ArXivPDFHTML

Papers citing "Disentangling the independently controllable factors of variation by interacting with the world"

41 / 41 papers shown
Title
Interpretable Machine Learning in Physics: A Review
Interpretable Machine Learning in Physics: A Review
Sebastian Johann Wetzel
Seungwoong Ha
Raban Iten
Miriam Klopotek
Ziming Liu
AI4CE
80
0
0
30 Mar 2025
Disentangled Representations for Causal Cognition
Disentangled Representations for Causal Cognition
Filippo Torresan
Manuel Baltieri
CML
37
1
0
30 Jun 2024
Memory Mosaics
Memory Mosaics
Jianyu Zhang
Niklas Nolte
Ranajoy Sadhukhan
Beidi Chen
Léon Bottou
VLM
73
3
0
10 May 2024
Algebras of actions in an agent's representations of the world
Algebras of actions in an agent's representations of the world
Alexander Dean
Eduardo Alonso
Esther Mondragón
33
0
0
02 Oct 2023
Reinforcement Learning with Exogenous States and Rewards
Reinforcement Learning with Exogenous States and Rewards
George Trimponias
Thomas G. Dietterich
OffRL
25
2
0
22 Mar 2023
Gromov-Wasserstein Autoencoders
Gromov-Wasserstein Autoencoders
Nao Nakagawa
Ren Togo
Takahiro Ogawa
Miki Haseyama
GAN
DRL
26
11
0
15 Sep 2022
elBERto: Self-supervised Commonsense Learning for Question Answering
elBERto: Self-supervised Commonsense Learning for Question Answering
Xunlin Zhan
Yuan Li
Xiao Dong
Xiaodan Liang
Zhiting Hu
Lawrence Carin
SSL
RALM
LRM
24
7
0
17 Mar 2022
Comparing Reconstruction- and Contrastive-based Models for Visual Task
  Planning
Comparing Reconstruction- and Contrastive-based Models for Visual Task Planning
Constantinos Chamzas
M. Lippi
Michael C. Welle
Anastasia Varava
Lydia E. Kavraki
Danica Kragic
SSL
DRL
OffRL
51
4
0
14 Sep 2021
Self-supervised Reinforcement Learning with Independently Controllable
  Subgoals
Self-supervised Reinforcement Learning with Independently Controllable Subgoals
Andrii Zadaianchuk
Georg Martius
Fanny Yang
SSL
64
16
0
09 Sep 2021
Desiderata for Representation Learning: A Causal Perspective
Desiderata for Representation Learning: A Causal Perspective
Yixin Wang
Michael I. Jordan
CML
32
80
0
08 Sep 2021
Discovering Generalizable Skills via Automated Generation of Diverse
  Tasks
Discovering Generalizable Skills via Automated Generation of Diverse Tasks
Kuan Fang
Yuke Zhu
Silvio Savarese
Li Fei-Fei
48
6
0
26 Jun 2021
Measuring Disentanglement: A Review of Metrics
Measuring Disentanglement: A Review of Metrics
M. Carbonneau
Julian Zaïdi
Jonathan Boilard
G. Gagnon
CoGe
DRL
28
81
0
16 Dec 2020
Self-supervised Visual Reinforcement Learning with Object-centric
  Representations
Self-supervised Visual Reinforcement Learning with Object-centric Representations
Andrii Zadaianchuk
Maximilian Seitzer
Georg Martius
SSL
OCL
27
41
0
29 Nov 2020
Affordance as general value function: A computational model
Affordance as general value function: A computational model
D. Graves
Johannes Günther
Jun Luo
AI4CE
21
6
0
27 Oct 2020
A Sober Look at the Unsupervised Learning of Disentangled
  Representations and their Evaluation
A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation
Francesco Locatello
Stefan Bauer
Mario Lucic
Gunnar Rätsch
Sylvain Gelly
Bernhard Schölkopf
Olivier Bachem
OOD
9
66
0
27 Oct 2020
A Disentangled Adversarial Neural Topic Model for Separating Opinions
  from Plots in User Reviews
A Disentangled Adversarial Neural Topic Model for Separating Opinions from Plots in User Reviews
Gabriele Pergola
Lin Gui
Yulan He
AAML
BDL
DRL
15
15
0
22 Oct 2020
RODE: Learning Roles to Decompose Multi-Agent Tasks
RODE: Learning Roles to Decompose Multi-Agent Tasks
Tonghan Wang
Tarun Gupta
Anuj Mahajan
Bei Peng
Shimon Whiteson
Chongjie Zhang
OffRL
30
39
0
04 Oct 2020
Revisiting Factorizing Aggregated Posterior in Learning Disentangled
  Representations
Revisiting Factorizing Aggregated Posterior in Learning Disentangled Representations
Ze Cheng
Juncheng Li
Chenxu Wang
Jixuan Gu
Hao Xu
Xinjian Li
Florian Metze
OOD
9
2
0
12 Sep 2020
Training Interpretable Convolutional Neural Networks by Differentiating
  Class-specific Filters
Training Interpretable Convolutional Neural Networks by Differentiating Class-specific Filters
Haoyun Liang
Zhihao Ouyang
Yuyuan Zeng
Hang Su
Zihao He
Shutao Xia
Jun Zhu
Bo Zhang
16
47
0
16 Jul 2020
Model-based Reinforcement Learning: A Survey
Model-based Reinforcement Learning: A Survey
Thomas M. Moerland
Joost Broekens
Aske Plaat
Catholijn M. Jonker
OffRL
27
47
0
30 Jun 2020
From proprioception to long-horizon planning in novel environments: A
  hierarchical RL model
From proprioception to long-horizon planning in novel environments: A hierarchical RL model
Nishad Gothoskar
Miguel Lázaro-Gredilla
Dileep George
23
0
0
11 Jun 2020
Stable Prediction via Leveraging Seed Variable
Stable Prediction via Leveraging Seed Variable
Kun Kuang
Yangqiu Song
Peng Cui
Yue Liu
Jianrong Tao
Yueting Zhuang
Fei Wu
OOD
CML
12
5
0
09 Jun 2020
PlaNet of the Bayesians: Reconsidering and Improving Deep Planning
  Network by Incorporating Bayesian Inference
PlaNet of the Bayesians: Reconsidering and Improving Deep Planning Network by Incorporating Bayesian Inference
Masashi Okada
Norio Kosaka
T. Taniguchi
8
43
0
01 Mar 2020
Resolving Spurious Correlations in Causal Models of Environments via
  Interventions
Resolving Spurious Correlations in Causal Models of Environments via Interventions
S. Volodin
Nevan Wichers
Jeremy Nixon
CML
17
16
0
12 Feb 2020
Weakly-Supervised Disentanglement Without Compromises
Weakly-Supervised Disentanglement Without Compromises
Francesco Locatello
Ben Poole
Gunnar Rätsch
Bernhard Schölkopf
Olivier Bachem
Michael Tschannen
CoGe
OOD
DRL
184
313
0
07 Feb 2020
Operationally meaningful representations of physical systems in neural
  networks
Operationally meaningful representations of physical systems in neural networks
Hendrik Poulsen Nautrup
Tony Metger
Raban Iten
Sofiene Jerbi
Lea M. Trenkwalder
H. Wilming
H. Briegel
R. Renner
AI4CE
NAI
11
25
0
02 Jan 2020
Deep Representation Learning in Speech Processing: Challenges, Recent
  Advances, and Future Trends
Deep Representation Learning in Speech Processing: Challenges, Recent Advances, and Future Trends
S. Latif
R. Rana
Sara Khalifa
Raja Jurdak
Junaid Qadir
Björn W. Schuller
AI4TS
32
81
0
02 Jan 2020
Contrastive Learning of Structured World Models
Contrastive Learning of Structured World Models
Thomas Kipf
Elise van der Pol
Max Welling
OCL
DRL
28
278
0
27 Nov 2019
Learning First-Order Symbolic Representations for Planning from the
  Structure of the State Space
Learning First-Order Symbolic Representations for Planning from the Structure of the State Space
Blai Bonet
Hector Geffner
NAI
4
53
0
12 Sep 2019
Dynamics-Aware Unsupervised Discovery of Skills
Dynamics-Aware Unsupervised Discovery of Skills
Archit Sharma
S. Gu
Sergey Levine
Vikash Kumar
Karol Hausman
16
398
0
02 Jul 2019
On the Fairness of Disentangled Representations
On the Fairness of Disentangled Representations
Francesco Locatello
G. Abbati
Tom Rainforth
Stefan Bauer
Bernhard Schölkopf
Olivier Bachem
FaML
DRL
15
227
0
31 May 2019
Locality-Promoting Representation Learning
Locality-Promoting Representation Learning
Johannes Schneider
12
2
0
25 May 2019
The Journey is the Reward: Unsupervised Learning of Influential
  Trajectories
The Journey is the Reward: Unsupervised Learning of Influential Trajectories
Jonathan Binas
Sherjil Ozair
Yoshua Bengio
SSL
14
4
0
22 May 2019
Disentangling Factors of Variation Using Few Labels
Disentangling Factors of Variation Using Few Labels
Francesco Locatello
Michael Tschannen
Stefan Bauer
Gunnar Rätsch
Bernhard Schölkopf
Olivier Bachem
DRL
CML
CoGe
29
123
0
03 May 2019
ToyArchitecture: Unsupervised Learning of Interpretable Models of the
  World
ToyArchitecture: Unsupervised Learning of Interpretable Models of the World
Jaroslav Vítků
Petr Dluhos
Joseph Davidson
Matej Nikl
Simon Andersson
...
Martin Stránský
M. Hyben
Martin Poliak
Jan Feyereisl
Marek Rosa
AI4CE
SSL
16
0
0
20 Mar 2019
Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps
  for Time Series Prediction
Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction
Bryan Lim
S. Zohren
Stephen J. Roberts
BDL
AI4TS
11
39
0
23 Jan 2019
Challenging Common Assumptions in the Unsupervised Learning of
  Disentangled Representations
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
Francesco Locatello
Stefan Bauer
Mario Lucic
Gunnar Rätsch
Sylvain Gelly
Bernhard Schölkopf
Olivier Bachem
OOD
11
1,445
0
29 Nov 2018
Towards Governing Agent's Efficacy: Action-Conditional $β$-VAE for
  Deep Transparent Reinforcement Learning
Towards Governing Agent's Efficacy: Action-Conditional βββ-VAE for Deep Transparent Reinforcement Learning
John Yang
Gyujeong Lee
Minsung Hyun
Simyung Chang
Nojun Kwak
13
3
0
11 Nov 2018
Curiosity Driven Exploration of Learned Disentangled Goal Spaces
Curiosity Driven Exploration of Learned Disentangled Goal Spaces
A. Laversanne-Finot
Alexandre Péré
Pierre-Yves Oudeyer
DRL
19
87
0
04 Jul 2018
Disentangling Controllable and Uncontrollable Factors of Variation by
  Interacting with the World
Disentangling Controllable and Uncontrollable Factors of Variation by Interacting with the World
Yoshihide Sawada
DRL
21
10
0
19 Apr 2018
Music Style Transfer: A Position Paper
Music Style Transfer: A Position Paper
Shuqi Dai
Zheng-Wei Zhang
Gus G. Xia
17
49
0
19 Mar 2018
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