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Differentiable Causal Discovery from Interventional Data
v1v2 (latest)

Differentiable Causal Discovery from Interventional Data

3 July 2020
P. Brouillard
Sébastien Lachapelle
Alexandre Lacoste
Simon Lacoste-Julien
Alexandre Drouin
    CML
ArXiv (abs)PDFHTML

Papers citing "Differentiable Causal Discovery from Interventional Data"

50 / 135 papers shown
Title
Flow-Based Non-stationary Temporal Regime Causal Structure Learning
Flow-Based Non-stationary Temporal Regime Causal Structure Learning
Abdellah Rahmani
P. Frossard
AI4TSCML
24
0
0
20 Jun 2025
Think Global, Act Local: Bayesian Causal Discovery with Language Models in Sequential Data
Think Global, Act Local: Bayesian Causal Discovery with Language Models in Sequential Data
Prakhar Verma
David Arbour
Sunav Choudhary
Harshita Chopra
Arno Solin
Atanu R. Sinha
10
0
0
19 Jun 2025
Causal Effect Identification in Heterogeneous Environments from Higher-Order Moments
Causal Effect Identification in Heterogeneous Environments from Higher-Order Moments
Yaroslav Kivva
S. Akbari
Saber Salehkaleybar
Negar Kiyavash
CML
29
0
0
13 Jun 2025
Causal Climate Emulation with Bayesian Filtering
Causal Climate Emulation with Bayesian Filtering
Sebastian Hickman
Ilija Trajkovic
Julia Kaltenborn
Francis Pelletier
Alex Archibald
Yaniv Gurwicz
Peer Nowack
David Rolnick
Julien Boussard
83
0
0
11 Jun 2025
Temporal Causal-based Simulation for Realistic Time-series Generation
Temporal Causal-based Simulation for Realistic Time-series Generation
Nikolaos Gkorgkolis
Nikolaos Kougioulis
Mingxue Wang
Bora Caglayan
Andrea Tonon
Dario Simionato
Ioannis Tsamardinos
CML
16
0
0
02 Jun 2025
Towards Identifiability of Interventional Stochastic Differential Equations
Towards Identifiability of Interventional Stochastic Differential Equations
Aaron Zweig
Zaikang Lin
Elham Azizi
David A. Knowles
75
1
0
21 May 2025
Bayesian Hierarchical Invariant Prediction
Bayesian Hierarchical Invariant Prediction
Francisco Madaleno
Pernille Julie Viuff Sand
Francisco C. Pereira
Sergio Hernan Garrido Mejia
74
0
0
16 May 2025
Representation Learning Preserving Ignorability and Covariate Matching for Treatment Effects
Representation Learning Preserving Ignorability and Covariate Matching for Treatment Effects
Praharsh Nanavati
Ranjitha Prasad
Karthikeyan Shanmugam
OODCML
125
0
0
29 Apr 2025
On the Identifiability of Causal Abstractions
Xiusi Li
Sékou-Oumar Kaba
Siamak Ravanbakhsh
CML
113
0
0
13 Mar 2025
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions
Juan L. Gamella
Armeen Taeb
C. Heinze-Deml
Peter Buhlmann
CML
187
8
0
13 Mar 2025
Can Large Language Models Help Experimental Design for Causal Discovery?
Junyi Li
Yongqiang Chen
Chenxi Liu
Qianyi Cai
Tongliang Liu
Bo Han
Kun Zhang
Hui Xiong
CML
95
2
0
03 Mar 2025
Extremely Greedy Equivalence Search
Extremely Greedy Equivalence Search
Achille Nazaret
David M. Blei
75
1
0
26 Feb 2025
Your Assumed DAG is Wrong and Here's How To Deal With It
Kirtan Padh
Zhufeng Li
Cecilia Casolo
Niki Kilbertus
CML
101
0
0
24 Feb 2025
Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery
Mateusz Olko
Mateusz Gajewski
Joanna Wojciechowska
Mikołaj Morzy
Piotr Sankowski
Piotr Miłoś
CML
102
0
0
22 Feb 2025
Causal Temporal Regime Structure Learning
Causal Temporal Regime Structure Learning
Abdellah Rahmani
Pascal Frossard
CML
256
2
0
20 Feb 2025
GPO-VAE: Modeling Explainable Gene Perturbation Responses utilizing GRN-Aligned Parameter Optimization
GPO-VAE: Modeling Explainable Gene Perturbation Responses utilizing GRN-Aligned Parameter Optimization
Seungheun Baek
Soyon Park
Y. T. Chok
Mogan Gim
Jaewoo Kang
DRL
77
0
0
31 Jan 2025
Causal Discovery via Bayesian Optimization
Bao Duong
Sunil Gupta
Thin Nguyen
157
0
0
28 Jan 2025
Interpretable Neural ODEs for Gene Regulatory Network Discovery under Perturbations
Interpretable Neural ODEs for Gene Regulatory Network Discovery under Perturbations
Zaikang Lin
Sei Chang
Aaron Zweig
Elham Azizi
David A. Knowles
David A. Knowles
134
1
0
05 Jan 2025
Causal-aware Graph Neural Architecture Search under Distribution Shifts
Causal-aware Graph Neural Architecture Search under Distribution Shifts
Peiwen Li
Xin Wang
Zeyang Zhang
Yi Qin
Ziwei Zhang
Jialong Wang
Yang Li
Wenwu Zhu
CMLOOD
147
4
0
31 Dec 2024
Differentiable Causal Discovery For Latent Hierarchical Causal Models
Differentiable Causal Discovery For Latent Hierarchical Causal Models
Parjanya Prashant
Ignavier Ng
Kun Zhang
Zhen Zhang
CML
338
0
0
29 Nov 2024
Generative Intervention Models for Causal Perturbation Modeling
Generative Intervention Models for Causal Perturbation Modeling
Nora Schneider
Lars Lorch
Niki Kilbertus
Bernhard Schölkopf
Andreas Krause
173
2
0
21 Nov 2024
SPARTAN: A Sparse Transformer Learning Local Causation
SPARTAN: A Sparse Transformer Learning Local Causation
Anson Lei
Bernhard Schölkopf
Ingmar Posner
100
3
0
11 Nov 2024
$ψ$DAG: Projected Stochastic Approximation Iteration for DAG
  Structure Learning
ψψψDAG: Projected Stochastic Approximation Iteration for DAG Structure Learning
Klea Ziu
Slavomír Hanzely
Loka Li
Kun Zhang
Martin Takáč
Dmitry Kamzolov
65
1
0
31 Oct 2024
Identifying Drift, Diffusion, and Causal Structure from Temporal Snapshots
Identifying Drift, Diffusion, and Causal Structure from Temporal Snapshots
Vincent Guan
Joseph Janssen
Hossein Rahmani
Andrew Warren
Stephen X. Zhang
Elina Robeva
Geoffrey Schiebinger
DiffM
131
7
0
30 Oct 2024
LLM-initialized Differentiable Causal Discovery
LLM-initialized Differentiable Causal Discovery
Shiv Kampani
David Hidary
Constantijn van der Poel
Martin Ganahl
Brenda Miao
67
1
0
28 Oct 2024
Revisiting Differentiable Structure Learning: Inconsistency of $\ell_1$
  Penalty and Beyond
Revisiting Differentiable Structure Learning: Inconsistency of ℓ1\ell_1ℓ1​ Penalty and Beyond
Kaifeng Jin
Ignavier Ng
Kun Zhang
Zhen Zhang
81
0
0
24 Oct 2024
CausalGraph2LLM: Evaluating LLMs for Causal Queries
CausalGraph2LLM: Evaluating LLMs for Causal Queries
Ivaxi Sheth
Bahare Fatemi
Mario Fritz
66
0
0
21 Oct 2024
LLM4GRN: Discovering Causal Gene Regulatory Networks with LLMs --
  Evaluation through Synthetic Data Generation
LLM4GRN: Discovering Causal Gene Regulatory Networks with LLMs -- Evaluation through Synthetic Data Generation
Tejumade Afonja
Ivaxi Sheth
Ruta Binkyte
Waqar Hanif
Thomas Ulas
Matthias Becker
Mario Fritz
113
3
0
21 Oct 2024
Learning to refine domain knowledge for biological network inference
Learning to refine domain knowledge for biological network inference
Peiwen Li
Menghua Wu
CML
79
1
0
18 Oct 2024
Efficient Differentiable Discovery of Causal Order
Efficient Differentiable Discovery of Causal Order
Mathieu Chevalley
Arash Mehrjou
Patrick Schwab
86
0
0
11 Oct 2024
Causal Representation Learning in Temporal Data via Single-Parent
  Decoding
Causal Representation Learning in Temporal Data via Single-Parent Decoding
Philippe Brouillard
Sébastien Lachapelle
Julia Kaltenborn
Yaniv Gurwicz
Dhanya Sridhar
Alexandre Drouin
Peer Nowack
Jakob Runge
David Rolnick
CML
61
6
0
09 Oct 2024
Markov Equivalence and Consistency in Differentiable Structure Learning
Markov Equivalence and Consistency in Differentiable Structure Learning
Chang Deng
Kevin Bello
Pradeep Ravikumar
Bryon Aragam
CML
147
0
0
08 Oct 2024
CAnDOIT: Causal Discovery with Observational and Interventional Data
  from Time-Series
CAnDOIT: Causal Discovery with Observational and Interventional Data from Time-Series
Luca Castri
Sariah Mghames
Marc Hanheide
Nicola Bellotto
CML
68
1
0
03 Oct 2024
Detecting and Measuring Confounding Using Causal Mechanism Shifts
Detecting and Measuring Confounding Using Causal Mechanism Shifts
Abbavaram Gowtham Reddy
Vineeth N Balasubramanian
CML
76
2
0
26 Sep 2024
Efficient Identification of Direct Causal Parents via Invariance and
  Minimum Error Testing
Efficient Identification of Direct Causal Parents via Invariance and Minimum Error Testing
Minh Le Nguyen
Mert R. Sabuncu
54
1
0
19 Sep 2024
Adapting to Shifting Correlations with Unlabeled Data Calibration
Adapting to Shifting Correlations with Unlabeled Data Calibration
Minh Le Nguyen
Alan Q. Wang
Heejong Kim
Mert R. Sabuncu
OOD
67
1
0
09 Sep 2024
Interventional Causal Structure Discovery over Graphical Models with
  Convergence and Optimality Guarantees
Interventional Causal Structure Discovery over Graphical Models with Convergence and Optimality Guarantees
Qiu Chengbo
Yang Kai
CML
88
0
0
09 Aug 2024
Visual Analysis of Multi-outcome Causal Graphs
Visual Analysis of Multi-outcome Causal Graphs
Mengjie Fan
Jinlu Yu
Daniel Weiskopf
Nan Cao
Huai-Yu Wang
Liang Zhou
CML
58
1
0
31 Jul 2024
Score matching through the roof: linear, nonlinear, and latent variables causal discovery
Score matching through the roof: linear, nonlinear, and latent variables causal discovery
Francesco Montagna
P. M. Faller
Patrick Bloebaum
Elke Kirschbaum
Francesco Locatello
CML
153
1
0
26 Jul 2024
LCA-on-the-Line: Benchmarking Out-of-Distribution Generalization with
  Class Taxonomies
LCA-on-the-Line: Benchmarking Out-of-Distribution Generalization with Class Taxonomies
Jia Shi
Gautam Gare
Jinjin Tian
Siqi Chai
Zhiqiu Lin
Arun Vasudevan
Di Feng
Francesco Ferroni
Shu Kong
VLMOODDOOD
100
6
0
22 Jul 2024
BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning
BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning
Hao-ming Lin
Wenhao Ding
Jian Chen
Laixi Shi
Jiacheng Zhu
Yue Liu
Ding Zhao
OffRLCML
123
0
0
15 Jul 2024
Spatio-Temporal Graphical Counterfactuals: An Overview
Spatio-Temporal Graphical Counterfactuals: An Overview
Mingyu Kang
Duxin Chen
Ziyuan Pu
Jianxi Gao
Wenwu Yu
CML
107
1
0
02 Jul 2024
Learning Flexible Time-windowed Granger Causality Integrating
  Heterogeneous Interventional Time Series Data
Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data
Ziyi Zhang
Shaogang Ren
Xiaoning Qian
Nick Duffield
AI4TSCML
69
3
0
14 Jun 2024
Scalable and Flexible Causal Discovery with an Efficient Test for
  Adjacency
Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency
Alan Nawzad Amin
Andrew Gordon Wilson
CML
111
1
0
13 Jun 2024
Interventional Causal Discovery in a Mixture of DAGs
Interventional Causal Discovery in a Mixture of DAGs
Burak Varıcı
Dmitriy A. Katz-Rogozhnikov
Dennis L. Wei
P. Sattigeri
A. Tajer
CML
86
1
0
12 Jun 2024
Fine-Grained Causal Dynamics Learning with Quantization for Improving
  Robustness in Reinforcement Learning
Fine-Grained Causal Dynamics Learning with Quantization for Improving Robustness in Reinforcement Learning
Inwoo Hwang
Yunhyeok Kwak
Suhyung Choi
Byoung-Tak Zhang
Sanghack Lee
110
1
0
05 Jun 2024
Knockout: A simple way to handle missing inputs
Knockout: A simple way to handle missing inputs
Minh Nguyen
Batuhan K. Karaman
Heejong Kim
Alan Q. Wang
Fengbei Liu
M. Sabuncu
OODUQCV
73
2
0
30 May 2024
Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm
Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm
Mathieu Chevalley
Patrick Schwab
Arash Mehrjou
141
1
0
28 May 2024
Demystifying amortized causal discovery with transformers
Demystifying amortized causal discovery with transformers
Francesco Montagna
Max Cairney-Leeming
Dhanya Sridhar
Francesco Locatello
CML
122
1
0
27 May 2024
Amortized Active Causal Induction with Deep Reinforcement Learning
Amortized Active Causal Induction with Deep Reinforcement Learning
Yashas Annadani
P. Tigas
Stefan Bauer
Adam Foster
76
1
0
26 May 2024
123
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