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2102.11107
Cited By
Towards Causal Representation Learning
22 February 2021
Bernhard Schölkopf
Francesco Locatello
Stefan Bauer
Nan Rosemary Ke
Nal Kalchbrenner
Anirudh Goyal
Yoshua Bengio
OOD
CML
AI4CE
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Papers citing
"Towards Causal Representation Learning"
33 / 83 papers shown
Title
Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies
Shachi Deshpande
Kaiwen Wang
Dhruv Sreenivas
Zheng Li
Volodymyr Kuleshov
CML
SyDa
16
11
0
18 Mar 2022
Reinforcement Learning in Practice: Opportunities and Challenges
Yuxi Li
OffRL
36
9
0
23 Feb 2022
CITRIS: Causal Identifiability from Temporal Intervened Sequences
Phillip Lippe
Sara Magliacane
Sindy Lowe
Yuki M. Asano
Taco S. Cohen
E. Gavves
CML
43
101
0
07 Feb 2022
Evaluation Methods and Measures for Causal Learning Algorithms
Lu Cheng
Ruocheng Guo
Raha Moraffah
Paras Sheth
K. S. Candan
Huan Liu
CML
ELM
24
51
0
07 Feb 2022
Unicorn: Reasoning about Configurable System Performance through the lens of Causality
Md Shahriar Iqbal
R. Krishna
Mohammad Ali Javidian
Baishakhi Ray
Pooyan Jamshidi
LRM
26
28
0
20 Jan 2022
Transferability in Deep Learning: A Survey
Junguang Jiang
Yang Shu
Jianmin Wang
Mingsheng Long
OOD
34
101
0
15 Jan 2022
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next
S. Cuomo
Vincenzo Schiano Di Cola
F. Giampaolo
G. Rozza
Maizar Raissi
F. Piccialli
PINN
26
1,180
0
14 Jan 2022
Towards Robust and Adaptive Motion Forecasting: A Causal Representation Perspective
Yuejiang Liu
Riccardo Cadei
Jonas Schweizer
Sherwin Bahmani
Alexandre Alahi
OOD
TTA
38
51
0
29 Nov 2021
Towards Principled Disentanglement for Domain Generalization
Hanlin Zhang
Yi-Fan Zhang
Weiyang Liu
Adrian Weller
Bernhard Schölkopf
Eric P. Xing
OOD
39
112
0
27 Nov 2021
Post-discovery Analysis of Anomalous Subsets
I. Mulang'
William Ogallo
G. Tadesse
Aisha Walcott-Bryant
29
1
0
23 Nov 2021
Exploration of Dark Chemical Genomics Space via Portal Learning: Applied to Targeting the Undruggable Genome and COVID-19 Anti-Infective Polypharmacology
Tian Cai
Li Xie
Muge Chen
Yang Liu
Di He
Shuo-feng Zhang
C. Mura
P. Bourne
Lei Xie
OOD
21
4
0
23 Nov 2021
Sparsely Changing Latent States for Prediction and Planning in Partially Observable Domains
Christian Gumbsch
Martin Volker Butz
Georg Martius
AI4CE
26
21
0
29 Oct 2021
Properties from Mechanisms: An Equivariance Perspective on Identifiable Representation Learning
Kartik Ahuja
Jason S. Hartford
Yoshua Bengio
29
38
0
29 Oct 2021
Distributionally Robust Recurrent Decoders with Random Network Distillation
Antonio Valerio Miceli Barone
Alexandra Birch
Rico Sennrich
31
1
0
25 Oct 2021
Dynamic Inference with Neural Interpreters
Nasim Rahaman
Muhammad Waleed Gondal
S. Joshi
Peter V. Gehler
Yoshua Bengio
Francesco Locatello
Bernhard Schölkopf
34
31
0
12 Oct 2021
Using Human-Guided Causal Knowledge for More Generalized Robot Task Planning
Semir Tatlidil
Yanqi Liu
Emily Sheetz
R. I. Bahar
Steven Sloman Brown University
24
0
0
09 Oct 2021
Target Languages (vs. Inductive Biases) for Learning to Act and Plan
Hector Geffner
42
6
0
15 Sep 2021
Reimagining an autonomous vehicle
Jeffrey Hawke
E. Haibo
Vijay Badrinarayanan
Alex Kendall
34
11
0
12 Aug 2021
Work in Progress -- Automated Generation of Robotic Planning Domains from Observations
Maximilian Diehl
Karinne Ramirez-Amaro
8
5
0
09 Jul 2021
Did I do that? Blame as a means to identify controlled effects in reinforcement learning
Oriol Corcoll
Youssef Mohamed
Raul Vicente
18
3
0
01 Jun 2021
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization
Damien Teney
Ehsan Abbasnejad
Simon Lucey
Anton Van Den Hengel
25
87
0
12 May 2021
What can the millions of random treatments in nonexperimental data reveal about causes?
Andre F. Ribeiro
Frank Neffke
Ricardo Hausmann
CML
28
1
0
03 May 2021
Domain Generalization: A Survey
Kaiyang Zhou
Ziwei Liu
Yu Qiao
Tao Xiang
Chen Change Loy
OOD
AI4CE
75
980
0
03 Mar 2021
Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling
Naoya Takeishi
Alexandros Kalousis
DRL
AI4CE
30
54
0
25 Feb 2021
On the Binding Problem in Artificial Neural Networks
Klaus Greff
Sjoerd van Steenkiste
Jürgen Schmidhuber
OCL
224
254
0
09 Dec 2020
On the Fairness of Causal Algorithmic Recourse
Julius von Kügelgen
Amir-Hossein Karimi
Umang Bhatt
Isabel Valera
Adrian Weller
Bernhard Schölkopf
FaML
80
82
0
13 Oct 2020
On Disentangled Representations Learned From Correlated Data
Frederik Trauble
Elliot Creager
Niki Kilbertus
Francesco Locatello
Andrea Dittadi
Anirudh Goyal
Bernhard Schölkopf
Stefan Bauer
OOD
CML
29
115
0
14 Jun 2020
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Sergey Levine
Aviral Kumar
George Tucker
Justin Fu
OffRL
GP
340
1,960
0
04 May 2020
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
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
359
11,684
0
09 Mar 2017
A Compositional Object-Based Approach to Learning Physical Dynamics
Michael Chang
T. Ullman
Antonio Torralba
J. Tenenbaum
AI4CE
OCL
241
438
0
01 Dec 2016
Interaction Networks for Learning about Objects, Relations and Physics
Peter W. Battaglia
Razvan Pascanu
Matthew Lai
Danilo Jimenez Rezende
Koray Kavukcuoglu
AI4CE
OCL
PINN
GNN
280
1,400
0
01 Dec 2016
From Ordinary Differential Equations to Structural Causal Models: the deterministic case
Joris Mooij
Dominik Janzing
Bernhard Schölkopf
74
101
0
09 Aug 2014
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