CASTLE: Regularization via Auxiliary Causal Graph Discovery

28 September 2020

Papers citing "CASTLE: Regularization via Auxiliary Causal Graph Discovery"

39 / 39 papers shown

Title
Urban Incident Prediction with Graph Neural Networks: Integrating Government Ratings and Crowdsourced Reports S. Balachandar Shuvom Sadhuka Bonnie Berger Emma Pierson Nikhil Garg AI4TS 19 0 0 10 Jun 2025
Markov Equivalence and Consistency in Differentiable Structure Learning Chang Deng Kevin Bello Pradeep Ravikumar Bryon Aragam CML 147 0 0 08 Oct 2024
Ordering-Based Causal Discovery for Linear and Nonlinear Relations Zhuopeng Xu Yujie Li Cheng Liu Ning Gui 55 2 0 08 Oct 2024
Towards Physically Consistent Deep Learning For Climate Model Parameterizations Birgit Kühbacher Fernando Iglesias-Suarez Niki Kilbertus Veronika Eyring AI4CE 48 1 0 06 Jun 2024
Embracing the black box: Heading towards foundation models for causal discovery from time series data Gideon Stein M. Shadaydeh Joachim Denzler CML AI4TS 59 2 0 14 Feb 2024
Boosting Causal Additive Models Maximilian Kertel Nadja Klein 76 0 0 12 Jan 2024
Online Handbook of Argumentation for AI: Volume 4 Lars Bengel Lydia Blümel Elfia Bezou-Vrakatseli Federico Castagna Giulia DÁgostino ... Daphne Odekerken Fabrizio Russo Stefan Sarkadi Madeleine Waller A. Xydis 58 0 0 20 Dec 2023
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 149 3 0 19 Dec 2023
Towards Human-like Perception: Learning Structural Causal Model in Heterogeneous Graph Tianqianjin Lin Kaisong Song Zhuoren Jiang Yangyang Kang Weikang Yuan Xurui Li Changlong Sun Cui Huang Xiaozhong Liu 82 6 0 10 Dec 2023
Enhancing the Performance of Neural Networks Through Causal Discovery and Integration of Domain Knowledge Xiaoge Zhang Xiao-Lin Wang Fenglei Fan Yiu-ming Cheung Indranil Bose 88 1 0 29 Nov 2023
A Review and Roadmap of Deep Causal Model from Different Causal Structures and Representations Hang Chen Keqing Du Chenguang Li Xinyu Yang 100 2 0 02 Nov 2023
Discovering Dynamic Causal Space for DAG Structure Learning Fan Liu Wenchang Ma An Zhang Xiang Wang Yueqi Duan Tat-Seng Chua OOD CML 39 2 0 05 Jun 2023
Towards Learning and Explaining Indirect Causal Effects in Neural Networks Abbaavaram Gowtham Reddy Saketh Bachu Harsh Nilesh Pathak Ben Godfrey V. Balasubramanian V. Varshaneya Satya Narayanan Kar CML 78 1 0 24 Mar 2023
Boosting Differentiable Causal Discovery via Adaptive Sample Reweighting An Zhang Fang Liu Wenchang Ma Zhibo Cai Xiang Wang Tat-Seng Chua CML 82 5 0 06 Mar 2023
Causal Deep Learning Jeroen Berrevoets Krzysztof Kacprzyk Zhaozhi Qian M. Schaar CML AI4CE 67 25 0 03 Mar 2023
CMVAE: Causal Meta VAE for Unsupervised Meta-Learning Guodong Qi Huimin Yu CML SSL 79 5 0 20 Feb 2023
Data-Driven Estimation of Heterogeneous Treatment Effects Christopher Tran Keith Burghardt Kristina Lerman Elena Zheleva CML 56 1 0 16 Jan 2023
Continual Causal Abstractions Matej Zečević Moritz Willig Jonas Seng Florian Peter Busch 64 1 0 23 Dec 2022
Navigating causal deep learning Jeroen Berrevoets Krzysztof Kacprzyk Zhaozhi Qian M. Schaar CML 85 2 0 01 Dec 2022
Neural Bayesian Network Understudy Paloma Rabaey Cedric De Boom Thomas Demeester BDL CML 63 0 0 15 Nov 2022
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 119 11 0 07 Nov 2022
GFlowCausal: Generative Flow Networks for Causal Discovery Wenqian Li Yinchuan Li Shengyu Zhu Yunfeng Shao Jianye Hao Yan Pang BDL CML 65 12 0 15 Oct 2022
DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization Kevin Bello Bryon Aragam Pradeep Ravikumar 115 84 0 16 Sep 2022
DAPDAG: Domain Adaptation via Perturbed DAG Reconstruction Yanke Li Hatt Tobias Ioana Bica M. Schaar CML 78 0 0 02 Aug 2022
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second Noah Hollmann Samuel G. Müller Katharina Eggensperger Frank Hutter 121 317 0 05 Jul 2022
Invariant Structure Learning for Better Generalization and Causal Explainability Yunhao Ge Sercan O. Arik Jinsung Yoon Ao Xu Laurent Itti Tomas Pfister OOD CML 49 2 0 13 Jun 2022
Differentiable and Transportable Structure Learning Jeroen Berrevoets Nabeel Seedat F. Imrie M. Schaar 87 2 0 13 Jun 2022
On the Generalization and Adaption Performance of Causal Models Nino Scherrer Anirudh Goyal Stefan Bauer Yoshua Bengio Nan Rosemary Ke CML OOD BDL TTA 80 8 0 09 Jun 2022
Causal Discovery and Knowledge Injection for Contestable Neural Networks (with Appendices) Fabrizio Russo Francesca Toni CML 57 7 0 19 May 2022
CausPref: Causal Preference Learning for Out-of-Distribution Recommendation Yue He Zimu Wang Peng Cui Hao Zou Yafeng Zhang Qiang Cui Yong Jiang OOD CML OODD 84 55 0 08 Feb 2022
Matching Learned Causal Effects of Neural Networks with Domain Priors Sai Srinivas Kancheti Abbavaram Gowtham Reddy V. Balasubramanian Amit Sharma CML 92 13 0 24 Nov 2021
MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms Trent Kyono Yao Zhang Alexis Bellot M. Schaar CML 104 66 0 04 Nov 2021
Simultaneous Missing Value Imputation and Structure Learning with Groups Pablo Morales-Álvarez Wenbo Gong A. Lamb Simon Woodhead Simon L. Peyton Jones Nick Pawlowski Miltiadis Allamanis Cheng Zhang 138 18 0 15 Oct 2021
Divide and Rule: Recurrent Partitioned Network for Dynamic Processes Qianyu Feng Bang Zhang Yi Yang 21 0 0 01 Jun 2021
Unsuitability of NOTEARS for Causal Graph Discovery Marcus Kaiser Maksim Sipos CML 109 66 0 12 Apr 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 147 305 0 03 Mar 2021
Incorporating Causal Graphical Prior Knowledge into Predictive Modeling via Simple Data Augmentation Takeshi Teshima Masashi Sugiyama CML 83 13 0 27 Feb 2021
Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge Trent Kyono Ioana Bica Zhaozhi Qian Mihaela van der Schaar OOD CML 28 7 0 11 Feb 2021
Inference of Causal Effects when Control Variables are Unknown Ludvig Hult Dave Zachariah CML 35 0 0 15 Dec 2020