Causal Regularization

28 June 2019

Papers citing "Causal Regularization"

17 / 17 papers shown

Title
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 69 1 0 24 Mar 2023
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second Noah Hollmann Samuel G. Müller Katharina Eggensperger Frank Hutter 119 316 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
Interpolation and Regularization for Causal Learning L. C. Vankadara Luca Rendsburg U. V. Luxburg Debarghya Ghoshdastidar CML 50 1 0 18 Feb 2022
Correcting Confounding via Random Selection of Background Variables You-Lin Chen Lenon Minorics Dominik Janzing CML 54 4 0 04 Feb 2022
On Causally Disentangled Representations Abbavaram Gowtham Reddy Benin Godfrey L V. Balasubramanian OOD CML 95 22 0 10 Dec 2021
Matching Learned Causal Effects of Neural Networks with Domain Priors Sai Srinivas Kancheti Abbavaram Gowtham Reddy V. Balasubramanian Amit Sharma CML 89 13 0 24 Nov 2021
Towards Causal Representation Learning Bernhard Schölkopf Francesco Locatello Stefan Bauer Nan Rosemary Ke Nal Kalchbrenner Anirudh Goyal Yoshua Bengio OOD CML AI4CE 152 322 0 22 Feb 2021
Generative Interventions for Causal Learning Chengzhi Mao Augustine Cha Amogh Gupta Hongya Wang Junfeng Yang Carl Vondrick CML OOD 79 66 0 22 Dec 2020
Invariant Representation Learning for Treatment Effect Estimation Claudia Shi Victor Veitch David M. Blei OOD CML 47 31 0 24 Nov 2020
Learning Causal Semantic Representation for Out-of-Distribution Prediction Chang-Shu Liu Xinwei Sun Jindong Wang Haoyue Tang Tao Li Tao Qin Wei Chen Tie-Yan Liu CML OODD OOD 140 106 0 03 Nov 2020
CASTLE: Regularization via Auxiliary Causal Graph Discovery Trent Kyono Yao Zhang M. Schaar OOD CML 66 69 0 28 Sep 2020
Learning explanations that are hard to vary Giambattista Parascandolo Alexander Neitz Antonio Orvieto Luigi Gresele Bernhard Schölkopf FAtt 86 187 0 01 Sep 2020
Causal Feature Selection via Orthogonal Search Ashkan Soleymani Anant Raj Stefan Bauer Bernhard Schölkopf M. Besserve CML 79 17 0 06 Jul 2020
Causality for Machine Learning Bernhard Schölkopf CML AI4CE LRM 106 464 0 24 Nov 2019
A Survey of Learning Causality with Data: Problems and Methods Ruocheng Guo Lu Cheng Jundong Li P. R. Hahn Huan Liu CML 77 169 0 25 Sep 2018
CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training Murat Kocaoglu Christopher Snyder A. Dimakis S. Vishwanath GAN OOD 107 257 0 06 Sep 2017