Causal Discovery Toolbox: Uncover causal relationships in Python

6 March 2019

Papers citing "Causal Discovery Toolbox: Uncover causal relationships in Python"

50 / 58 papers shown

Title
Differentially Private and Federated Structure Learning in Bayesian Networks Ghita Fassy El Fehri Aurélien Bellet Philippe Bastien FedML 162 0 0 01 Dec 2025
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 OOD CML 158 0 0 14 Oct 2025
OCDB: Revisiting Causal Discovery with a Comprehensive Benchmark and Evaluation Framework Wei Zhou Hong Huang Guowen Zhang Ruize Shi Kehan Yin Yuanyuan Lin Bang Liu CML 229 1 0 07 Jun 2024
CausalPlayground: Addressing Data-Generation Requirements in Cutting-Edge Causality Research Andreas Sauter Erman Acar Aske Plaat SyDa CML 238 3 0 21 May 2024
Generalized Criterion for Identifiability of Additive Noise Models Using Majorization Aramayis Dallakyan Yang Ni CML 263 0 0 08 Apr 2024
ChatDiet: Empowering Personalized Nutrition-Oriented Food Recommender Chatbots through an LLM-Augmented Framework Zhongqi Yang Elahe Khatibi N. Nagesh Mahyar Abbasian Iman Azimi Ramesh C. Jain Amir M. Rahmani 283 76 0 18 Feb 2024
Causal Discovery by Kernel Deviance Measures with Heterogeneous Transforms Tim Tse Zhitang Chen Shengyu Zhu Yue Liu CML 110 0 0 31 Jan 2024
Accelerating Causal Algorithms for Industrial-scale Data: A Distributed Computing Approach with Ray FrameworkInternational Conference on AI-ML-Systems (ICA), 2023 Vishal Verma Vinod Reddy Jaiprakash Ravi 184 1 0 22 Jan 2024
Can We Utilize Pre-trained Language Models within Causal Discovery Algorithms? Chanhui Lee Juhyeon Kim Yongjun Jeong Juhyun Lyu Junghee Kim ... Hyeokjun Choe Soyeon Park Woohyung Lim Sungbin Lim Snu Astronomy Research Center 153 1 0 19 Nov 2023
CRAB: Assessing the Strength of Causal Relationships Between Real-world Events Angelika Romanou Syrielle Montariol Debjit Paul Leo Laugier Karl Aberer Antoine Bosselut NAI 155 32 0 07 Nov 2023
UPREVE: An End-to-End Causal Discovery Benchmarking System Suraj Jyothi Unni Paras Sheth Kaize Ding Huan Liu K. S. Candan CML 139 0 0 25 Jul 2023
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation Chris C. Emezue Alexandre Drouin T. Deleu Stefan Bauer Yoshua Bengio CML 324 2 0 11 Jul 2023
Learning Causal Graphs via Monotone Triangular Transport Maps S. Akbari Luca Ganassali Negar Kiyavash OT CML 147 8 0 26 May 2023
Learning DAGs from Data with Few Root CausesNeural Information Processing Systems (NeurIPS), 2023 Panagiotis Misiakos Chris Wendler Markus Püschel CML 354 13 0 25 May 2023
A Survey on Causal Discovery: Theory and PracticeInternational Journal of Approximate Reasoning (IJAR), 2022 Alessio Zanga Elif Ozkirimli Fabio Stella CML 253 107 0 17 May 2023
Causal Discovery and Optimal Experimental Design for Genome-Scale Biological Network RecoveryPlatform for Advanced Scientific Computing Conference (PASC), 2023 Ashka Shah A. Ramanathan Valérie Hayot-Sasson Rick L. Stevens CML 78 2 0 06 Apr 2023
A Survey on Causal Discovery Methods for I.I.D. and Time Series Data Uzma Hasan Emam Hossain Md. Osman Gani CML AI4TS 535 47 0 27 Mar 2023
DAG Learning on the PermutahedronInternational Conference on Learning Representations (ICLR), 2023 Valentina Zantedeschi Luca Franceschi Jean Kaddour Matt J. Kusner Vlad Niculae 271 11 0 27 Jan 2023
Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data Devansh Arpit M. Fernández Itai Feigenbaum Weiran Yao Chenghao Liu ... Haiquan Wang Stephen Hoi Caiming Xiong Kun Zhang Juan Carlos Niebles CML 144 2 0 25 Jan 2023
Towards Privacy-Aware Causal Structure Learning in Federated SettingIEEE Transactions on Big Data (TBD), 2022 Jianli Huang Xianjie Guo Kui Yu Fuyuan Cao Jiye Liang FedML 282 14 0 13 Nov 2022
Causal Explanation for Reinforcement Learning: Quantifying State and Temporal Importance Xiaoxiao Wang Fanyu Meng Xin Liu Z. Kong Xin Chen XAI CML FAtt 321 4 0 24 Oct 2022
Granger Causal Chain Discovery for Sepsis-Associated Derangements via Continuous-Time Hawkes ProcessesKnowledge Discovery and Data Mining (KDD), 2022 S. Wei Yao Xie C. Josef Rishikesan Kamaleswaran 330 11 0 09 Sep 2022
Truncated Matrix Power Iteration for Differentiable DAG LearningNeural Information Processing Systems (NeurIPS), 2022 Zhen Zhang Ignavier Ng Dong Gong Yuhang Liu Ehsan Abbasnejad Biwei Huang Kun Zhang Javen Qinfeng Shi 263 30 0 30 Aug 2022
D-BIAS: A Causality-Based Human-in-the-Loop System for Tackling Algorithmic BiasIEEE Transactions on Visualization and Computer Graphics (TVCG), 2022 Bhavya Ghai Klaus Mueller 164 50 0 10 Aug 2022
CIPCaD-Bench: Continuous Industrial Process datasets for benchmarking Causal Discovery methods Giovanni Menegozzo Diego DallÁlba Paolo Fiorini 308 9 0 02 Aug 2022
A Meta-Reinforcement Learning Algorithm for Causal DiscoveryCLEaR (CLEaR), 2022 Andreas Sauter Erman Acar Vincent François-Lavet CML 264 20 0 18 Jul 2022
Reframed GES with a Neural Conditional Dependence MeasureConference on Uncertainty in Artificial Intelligence (UAI), 2022 Xinwei Shen Shengyu Zhu Jiji Zhang Shoubo Hu Zhitang Chen CML 145 3 0 17 Jun 2022
Large-Scale Differentiable Causal Discovery of Factor GraphsNeural Information Processing Systems (NeurIPS), 2022 Romain Lopez Jan-Christian Hütter J. Pritchard Aviv Regev CML AI4CE 358 56 0 15 Jun 2022
DoWhy-GCM: An extension of DoWhy for causal inference in graphical causal modelsJournal of machine learning research (JMLR), 2022 Patrick Blobaum P. Götz Kailash Budhathoki Atalanti A. Mastakouri Dominik Janzing 137 76 0 14 Jun 2022
Causal Discovery for Fairness Ruta Binkyt.e-Sadauskien.e K. Makhlouf Carlos Pinzón Sami Zhioua C. Palamidessi CML 208 23 0 14 Jun 2022
Active Bayesian Causal InferenceNeural Information Processing Systems (NeurIPS), 2022 Christian Toth Lars Lorch Christian Knoll Andreas Krause Franz Pernkopf Robert Peharz Julius von Kügelgen 256 40 0 04 Jun 2022
BaCaDI: Bayesian Causal Discovery with Unknown InterventionsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 Alexander Hagele Jonas Rothfuss Lars Lorch Vignesh Ram Somnath Bernhard Schölkopf Andreas Krause CML BDL 294 28 0 03 Jun 2022
Do learned representations respect causal relationships?Computer Vision and Pattern Recognition (CVPR), 2022 Lan Wang Vishnu Boddeti NAI CML OOD 258 8 0 02 Apr 2022
Evaluation Methods and Measures for Causal Learning AlgorithmsIEEE Transactions on Artificial Intelligence (IEEE TAI), 2022 Lu Cheng Ruocheng Guo Raha Moraffah Paras Sheth K. S. Candan Huan Liu CML ELM 232 71 0 07 Feb 2022
BCDAG: An R package for Bayesian structure and Causal learning of Gaussian DAGs F. Castelletti Alessandro Mascaro CML 143 5 0 28 Jan 2022
Unifying Pairwise Interactions in Complex DynamicsNature Computational Science (Nat. Comput. Sci.), 2022 Oliver M. Cliff Annie G. Bryant J. Lizier N. Tsuchiya Ben D. Fulcher 236 65 0 28 Jan 2022
Identifying Causal Influences on Publication Trends and Behavior: A Case Study of the Computational Linguistics Community M. Glenski Svitlana Volkova CML AI4CE 176 1 0 15 Oct 2021
ML4C: Seeing Causality Through Latent Vicinity Haoyue Dai Rui Ding Yuanyuan Jiang Shi Han Dongmei Zhang OOD 253 14 0 01 Oct 2021
A Fast PC Algorithm with Reversed-order Pruning and A Parallelization Strategy Kai Zhang Chao Tian Kun Zhang Todd Johnson Xiaoqian Jiang CML 154 4 0 10 Sep 2021
Learning Neural Causal Models with Active Interventions Nino Scherrer O. Bilaniuk Yashas Annadani Anirudh Goyal Patrick Schwab Bernhard Schölkopf Michael C. Mozer Yoshua Bengio Stefan Bauer Nan Rosemary Ke CML 309 50 0 06 Sep 2021
Model-Based Counterfactual Synthesizer for Interpretation Fan Yang Sahan Suresh Alva Jiahao Chen X. Hu 98 34 0 16 Jun 2021
Marginalizable Density Models D. Gilboa Ari Pakman Thibault Vatter BDL 163 5 0 08 Jun 2021
DiBS: Differentiable Bayesian Structure LearningNeural Information Processing Systems (NeurIPS), 2021 Lars Lorch Jonas Rothfuss Bernhard Schölkopf Andreas Krause 368 112 0 25 May 2021
D'ya like DAGs? A Survey on Structure Learning and Causal DiscoveryACM Computing Surveys (CSUR), 2021 M. Vowels Necati Cihan Camgöz Richard Bowden CML 483 350 0 03 Mar 2021
BeFair: Addressing Fairness in the Banking Sector Alessandro Castelnovo Riccardo Crupi Giulia Del Gamba Greta Greco A. Naseer D. Regoli Beatriz San Miguel González FaML 108 19 0 03 Feb 2021
A Bregman Method for Structure Learning on Sparse Directed Acyclic Graphs Manon Romain Alexandre d’Aspremont 167 5 0 05 Nov 2020
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian NetworksNeural Information Processing Systems (NeurIPS), 2020 Dennis L. Wei Tian Gao Yue Yu CML 218 86 0 18 Oct 2020
CausalFlow: Visual Analytics of Causality in Event Sequences Xiao Xie Moqi He Yingcai Wu AI4TS 838 6 0 27 Aug 2020
Causal Adversarial Network for Learning Conditional and Interventional Distributions Raha Moraffah Bahman Moraffah Mansooreh Karami A. Raglin Huan Liu OOD GAN CML 175 22 0 26 Aug 2020
Information-Theoretic Approximation to Causal Models Peter Gmeiner 133 0 0 29 Jul 2020