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CITRIS: Causal Identifiability from Temporal Intervened Sequences

CITRIS: Causal Identifiability from Temporal Intervened Sequences

7 February 2022
Phillip Lippe
Sara Magliacane
Sindy Lowe
Yuki M. Asano
Taco S. Cohen
E. Gavves
    CML
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Papers citing "CITRIS: Causal Identifiability from Temporal Intervened Sequences"

19 / 19 papers shown
Title
Causal View of Time Series Imputation: Some Identification Results on Missing Mechanism
Causal View of Time Series Imputation: Some Identification Results on Missing Mechanism
Ruichu Cai
Kaitao Zheng
Junxian Huang
Zijian Li
Zhengming Chen
Boyan Xu
Zhifeng Hao
AI4TS
CML
31
0
0
12 May 2025
Learning Local Causal World Models with State Space Models and Attention
Learning Local Causal World Models with State Space Models and Attention
Francesco Petri
Luigi Asprino
Aldo Gangemi
CML
40
0
0
04 May 2025
Negate or Embrace: On How Misalignment Shapes Multimodal Representation Learning
Negate or Embrace: On How Misalignment Shapes Multimodal Representation Learning
Yichao Cai
Yuhang Liu
Erdun Gao
T. Jiang
Zhen Zhang
Anton van den Hengel
J. Shi
62
0
0
14 Apr 2025
Sanity Checking Causal Representation Learning on a Simple Real-World System
Sanity Checking Causal Representation Learning on a Simple Real-World System
Juan L. Gamella
Simon Bing
Jakob Runge
CML
50
0
0
27 Feb 2025
What is causal about causal models and representations?
What is causal about causal models and representations?
Frederik Hytting Jørgensen
Luigi Gresele
S. Weichwald
CML
105
0
0
31 Jan 2025
All or None: Identifiable Linear Properties of Next-token Predictors in Language Modeling
All or None: Identifiable Linear Properties of Next-token Predictors in Language Modeling
Emanuele Marconato
Sébastien Lachapelle
Sebastian Weichwald
Luigi Gresele
66
3
0
30 Oct 2024
A Complexity-Based Theory of Compositionality
A Complexity-Based Theory of Compositionality
Eric Elmoznino
Thomas Jiralerspong
Yoshua Bengio
Guillaume Lajoie
CoGe
61
4
0
18 Oct 2024
Towards a Unified Framework of Contrastive Learning for Disentangled
  Representations
Towards a Unified Framework of Contrastive Learning for Disentangled Representations
Stefan Matthes
Zhiwei Han
Hao Shen
31
4
0
08 Nov 2023
Causal Representation Learning Made Identifiable by Grouping of
  Observational Variables
Causal Representation Learning Made Identifiable by Grouping of Observational Variables
H. Morioka
Aapo Hyvarinen
OOD
CML
BDL
33
9
0
24 Oct 2023
Nonparametric Identifiability of Causal Representations from Unknown
  Interventions
Nonparametric Identifiability of Causal Representations from Unknown Interventions
Julius von Kügelgen
M. Besserve
Wendong Liang
Luigi Gresele
Armin Kekić
Elias Bareinboim
David M. Blei
Bernhard Schölkopf
CML
18
56
0
01 Jun 2023
Enhancing Causal Discovery from Robot Sensor Data in Dynamic Scenarios
Enhancing Causal Discovery from Robot Sensor Data in Dynamic Scenarios
Luca Castri
Sariah Mghames
Marc Hanheide
Nicola Bellotto
CML
29
10
0
20 Feb 2023
Causal Triplet: An Open Challenge for Intervention-centric Causal
  Representation Learning
Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning
Yuejiang Liu
Alexandre Alahi
Chris Russell
Max Horn
Dominik Zietlow
Bernhard Schölkopf
Francesco Locatello
CML
56
22
0
12 Jan 2023
Deep Causal Learning: Representation, Discovery and Inference
Deep Causal Learning: Representation, Discovery and Inference
Zizhen Deng
Xiaolong Zheng
Hu Tian
D. Zeng
CML
BDL
31
11
0
07 Nov 2022
Temporally Disentangled Representation Learning
Temporally Disentangled Representation Learning
Weiran Yao
Guangyi Chen
Kun Zhang
CML
BDL
OOD
23
48
0
24 Oct 2022
Causal Discovery in Heterogeneous Environments Under the Sparse
  Mechanism Shift Hypothesis
Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis
Ronan Perry
Julius von Kügelgen
Bernhard Schölkopf
41
48
0
04 Jun 2022
Weakly Supervised Representation Learning with Sparse Perturbations
Weakly Supervised Representation Learning with Sparse Perturbations
Kartik Ahuja
Jason S. Hartford
Yoshua Bengio
SSL
35
58
0
02 Jun 2022
Weakly supervised causal representation learning
Weakly supervised causal representation learning
Johann Brehmer
P. D. Haan
Phillip Lippe
Taco S. Cohen
OOD
CML
30
120
0
30 Mar 2022
Contrastive Learning Inverts the Data Generating Process
Contrastive Learning Inverts the Data Generating Process
Roland S. Zimmermann
Yash Sharma
Steffen Schneider
Matthias Bethge
Wieland Brendel
SSL
238
207
0
17 Feb 2021
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
178
313
0
07 Feb 2020
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