CASTLE: Regularization via Auxiliary Causal Graph Discovery

28 September 2020

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

23 / 23 papers shown

Title
Boosting Causal Additive Models Maximilian Kertel Nadja Klein 52 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 43 0 0 20 Dec 2023
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 56 2 0 19 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 51 1 0 29 Nov 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 36 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 53 5 0 06 Mar 2023
Causal Deep Learning Jeroen Berrevoets Krzysztof Kacprzyk Zhaozhi Qian M. Schaar CML AI4CE 26 25 0 03 Mar 2023
Data-Driven Estimation of Heterogeneous Treatment Effects Christopher Tran Keith Burghardt Kristina Lerman Elena Zheleva CML 32 1 0 16 Jan 2023
Navigating causal deep learning Jeroen Berrevoets Krzysztof Kacprzyk Zhaozhi Qian M. Schaar CML 46 2 0 01 Dec 2022
Neural Bayesian Network Understudy Paloma Rabaey Cedric De Boom Thomas Demeester BDL CML 38 0 0 15 Nov 2022
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 51 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 16 12 0 15 Oct 2022
DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization Kevin Bello Bryon Aragam Pradeep Ravikumar 66 79 0 16 Sep 2022
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second Noah Hollmann Samuel G. Müller Katharina Eggensperger Frank Hutter 43 270 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 40 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 44 8 0 09 Jun 2022
Matching Learned Causal Effects of Neural Networks with Domain Priors Sai Srinivas Kancheti Abbavaram Gowtham Reddy V. Balasubramanian Amit Sharma CML 41 13 0 24 Nov 2021
MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms Trent Kyono Yao Zhang Alexis Bellot M. Schaar CML 49 61 0 04 Nov 2021
Unsuitability of NOTEARS for Causal Graph Discovery Marcus Kaiser Maksim Sipos CML 57 65 0 12 Apr 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 52 297 0 03 Mar 2021
Learning Sparse Nonparametric DAGs Xun Zheng Chen Dan Bryon Aragam Pradeep Ravikumar Eric Xing CML 119 257 0 29 Sep 2019
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 316 2,904 0 15 Sep 2016
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 270 7,641 0 03 Jul 2012