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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
Damien Scieur
Alexandre Drouin
    CML
ArXiv (abs)PDFHTML

Papers citing "Differentiable Causal Discovery from Interventional Data"

50 / 155 papers shown
Does TabPFN Understand Causal Structures?
Does TabPFN Understand Causal Structures?
Omar Swelam
Lennart Purucker
Jake Robertson
Hanne Raum
Joschka Boedecker
Frank Hutter
CML
276
3
0
10 Nov 2025
Robust Causal Discovery under Imperfect Structural Constraints
Robust Causal Discovery under Imperfect Structural Constraints
Zidong Wang
Xi Lin
Chuchao He
Xiaoguang Gao
CML
265
0
0
10 Nov 2025
Theoretical Guarantees for Causal Discovery on Large Random Graphs
Theoretical Guarantees for Causal Discovery on Large Random Graphs
Mathieu Chevalley
Arash Mehrjou
Patrick Schwab
CML
244
0
0
04 Nov 2025
Linear Causal Discovery with Interventional Constraints
Linear Causal Discovery with Interventional Constraints
Zhigao Guo
Feng Dong
CML
170
0
0
30 Oct 2025
MetaCaDI: A Meta-Learning Framework for Scalable Causal Discovery with Unknown Interventions
MetaCaDI: A Meta-Learning Framework for Scalable Causal Discovery with Unknown Interventions
Hans Jarett Ong
Yoichi Chikahara
Tomoharu Iwata
CMLBDL
211
0
0
25 Oct 2025
Bridging Prediction and Attribution: Identifying Forward and Backward Causal Influence Ranges Using Assimilative Causal Inference
Bridging Prediction and Attribution: Identifying Forward and Backward Causal Influence Ranges Using Assimilative Causal Inference
Marios Andreou
Nan Chen
CML
169
0
0
24 Oct 2025
InvarGC: Invariant Granger Causality for Heterogeneous Interventional Time Series under Latent Confounding
InvarGC: Invariant Granger Causality for Heterogeneous Interventional Time Series under Latent Confounding
Ziyi Zhang
Shaogang Ren
Xiaoning Qian
N. Duffield
156
0
0
22 Oct 2025
Simulation-free Structure Learning for Stochastic Dynamics
Simulation-free Structure Learning for Stochastic Dynamics
Noah El Rimawi-Fine
Adam Stecklov
Lucas Nelson
Mathieu Blanchette
Alexander Tong
Stephen Y. Zhang
Lazar Atanackovic
AI4CE
194
1
0
18 Oct 2025
On the identifiability of causal graphs with multiple environments
On the identifiability of causal graphs with multiple environments
Francesco Montagna
CML
369
1
0
15 Oct 2025
The Robustness of Differentiable Causal Discovery in Misspecified Scenarios
The Robustness of Differentiable Causal Discovery in Misspecified ScenariosInternational Conference on Learning Representations (ICLR), 2025
Huiyang Yi
Yanyan He
Duxin Chen
Mingyu Kang
He Wang
Wenwu Yu
OODCML
224
2
0
14 Oct 2025
DODO: Causal Structure Learning with Budgeted Interventions
DODO: Causal Structure Learning with Budgeted Interventions
Matteo Gregorini
Chiara Boldrini
Lorenzo Valerio
CML
180
0
0
09 Oct 2025
Score-based Greedy Search for Structure Identification of Partially Observed Linear Causal Models
Score-based Greedy Search for Structure Identification of Partially Observed Linear Causal Models
Xinshuai Dong
Ignavier Ng
Haoyue Dai
Jiaqi Sun
Xiangchen Song
Peter Spirtes
Kun Zhang
CML
162
1
0
05 Oct 2025
DAG DECORation: Continuous Optimization for Structure Learning under Hidden Confounding
DAG DECORation: Continuous Optimization for Structure Learning under Hidden Confounding
Samhita Pal
James O'quinn
Kaveh Aryan
Heather Pua
James P. Long
Amir Asiaee
CML
185
3
0
02 Oct 2025
Large-Scale Bayesian Causal Discovery with Interventional Data
Large-Scale Bayesian Causal Discovery with Interventional Data
Seong Woo Han
Daniel Duy Vo
Brielin C. Brown
CML
143
0
0
02 Oct 2025
Dual Optimistic Ascent (PI Control) is the Augmented Lagrangian Method in Disguise
Dual Optimistic Ascent (PI Control) is the Augmented Lagrangian Method in Disguise
Juan Ramirez
Damien Scieur
174
1
0
26 Sep 2025
Effects of Distributional Biases on Gradient-Based Causal Discovery in the Bivariate Categorical Case
Effects of Distributional Biases on Gradient-Based Causal Discovery in the Bivariate Categorical Case
Tim Schwabe
Moritz Lange
Laurenz Wiskott
Maribel Acosta
CML
244
0
0
01 Sep 2025
Differentiable Cyclic Causal Discovery Under Unmeasured Confounders
Differentiable Cyclic Causal Discovery Under Unmeasured Confounders
Muralikrishnna G. Sethuraman
Faramarz Fekri
CML
173
2
0
11 Aug 2025
From Observations to Causations: A GNN-based Probabilistic Prediction Framework for Causal Discovery
From Observations to Causations: A GNN-based Probabilistic Prediction Framework for Causal Discovery
Rezaur Rashid
G. Terejanu
CMLBDL
202
0
0
27 Jul 2025
Curious Causality-Seeking Agents Learn Meta Causal World
Curious Causality-Seeking Agents Learn Meta Causal World
Zhiyu Zhao
Xue Yang
Haifeng Zhang
Jun Wang
Francesco Faccio
Jürgen Schmidhuber
Mengyue Yang
CMLLRM
378
1
0
29 Jun 2025
Flow based approach for Dynamic Temporal Causal models with non-Gaussian or Heteroscedastic Noises
Flow based approach for Dynamic Temporal Causal models with non-Gaussian or Heteroscedastic Noises
Abdellah Rahmani
P. Frossard
AI4TSCML
315
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
319
0
0
19 Jun 2025
Causal Effect Identification in Heterogeneous Environments from Higher-Order Moments
Causal Effect Identification in Heterogeneous Environments from Higher-Order MomentsConference on Uncertainty in Artificial Intelligence (UAI), 2025
Yaroslav Kivva
S. Akbari
Saber Salehkaleybar
Negar Kiyavash
CML
324
2
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
406
3
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
304
2
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
470
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
422
2
0
16 May 2025
Characterization and Learning of Causal Graphs from Hard Interventions
Characterization and Learning of Causal Graphs from Hard Interventions
Zihan Zhou
Muhammad Qasim Elahi
Murat Kocaoglu
CML
564
1
0
02 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
325
0
0
29 Apr 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
552
12
0
13 Mar 2025
On the Identifiability of Causal Abstractions
On the Identifiability of Causal AbstractionsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Xiusi Li
Sékou-Oumar Kaba
Siamak Ravanbakhsh
CML
406
1
0
13 Mar 2025
Can Large Language Models Help Experimental Design for Causal Discovery?
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
430
8
0
03 Mar 2025
Extremely Greedy Equivalence Search
Extremely Greedy Equivalence SearchConference on Uncertainty in Artificial Intelligence (UAI), 2025
Achille Nazaret
David M. Blei
295
7
0
26 Feb 2025
Your Assumed DAG is Wrong and Here's How To Deal With It
Your Assumed DAG is Wrong and Here's How To Deal With ItCLEaR (CLEaR), 2025
Kirtan Padh
Zhufeng Li
Cecilia Casolo
Niki Kilbertus
CML
507
1
0
24 Feb 2025
Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery
Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery
Mateusz Olko
Mateusz Gajewski
Joanna Wojciechowska
Mikołaj Morzy
Piotr Sankowski
Piotr Miłoś
CML
389
3
0
22 Feb 2025
Causal Temporal Regime Structure Learning
Causal Temporal Regime Structure LearningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Abdellah Rahmani
Pascal Frossard
CML
621
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 OptimizationBioinformatics (Bioinformatics), 2025
Seungheun Baek
Soyon Park
Y. T. Chok
Mogan Gim
Jaewoo Kang
DRL
389
0
0
31 Jan 2025
Causal Discovery via Bayesian Optimization
Causal Discovery via Bayesian OptimizationInternational Conference on Learning Representations (ICLR), 2025
Bao Duong
Sunil Gupta
Thin Nguyen
387
1
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
Minseo Kang
Elham Azizi
David A. Knowles
612
7
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
384
7
0
31 Dec 2024
Differentiable Causal Discovery For Latent Hierarchical Causal Models
Differentiable Causal Discovery For Latent Hierarchical Causal ModelsInternational Conference on Learning Representations (ICLR), 2024
Parjanya Prashant
Ignavier Ng
Kun Zhang
Zhen Zhang
CML
645
2
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
531
5
0
21 Nov 2024
SPARTAN: A Sparse Transformer World Model Attending to What Matters
SPARTAN: A Sparse Transformer World Model Attending to What Matters
Anson Lei
Bernhard Schölkopf
Ingmar Posner
CML
666
6
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
365
4
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
554
13
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
399
4
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
388
0
0
24 Oct 2024
CausalGraph2LLM: Evaluating LLMs for Causal Queries
CausalGraph2LLM: Evaluating LLMs for Causal QueriesNorth American Chapter of the Association for Computational Linguistics (NAACL), 2024
Ivaxi Sheth
Bahare Fatemi
Mario Fritz
221
10
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
345
8
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
244
2
0
18 Oct 2024
Efficient Differentiable Discovery of Causal Order
Efficient Differentiable Discovery of Causal Order
Mathieu Chevalley
Arash Mehrjou
Patrick Schwab
390
1
0
11 Oct 2024
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