Causality for Machine Learning

24 November 2019

Papers citing "Causality for Machine Learning"

50 / 97 papers shown

Title
Mitigating Spurious Correlations with Causal Logit Perturbation Xiaoling Zhou Wei Ye Rui Xie Shikun Zhang CML 14 0 0 21 May 2025
Q-function Decomposition with Intervention Semantics with Factored Action Spaces Junkyu Lee Tian Gao Elliot Nelson Miao Liu D. Bhattacharjya Songtao Lu OffRL 50 0 0 30 Apr 2025
On the Role of Priors in Bayesian Causal Learning Bernhard C. Geiger Roman Kern CML 39 0 0 02 Apr 2025
Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models Ruta Binkyte Ivaxi Sheth Zhijing Jin Mohammad Havaei Bernhard Schölkopf Mario Fritz 215 0 0 28 Feb 2025
Reducing Action Space for Deep Reinforcement Learning via Causal Effect Estimation Wenzhang Liu Lianjun Jin Lu Ren Chaoxu Mu Changyin Sun CML 53 0 0 24 Jan 2025
Probabilistic Parameter Estimators and Calibration Metrics for Pose Estimation from Image Features Romeo Valentin Sydney M. Katz Joonghyun Lee Don Walker Matthew Sorgenfrei Mykel J. Kochenderfer 36 0 0 23 Jul 2024
Standardizing Structural Causal Models Weronika Ormaniec Scott Sussex Lars Lorch Bernhard Schölkopf Andreas Krause CML 58 5 0 17 Jun 2024
Local Causal Structure Learning in the Presence of Latent Variables Feng Xie Zheng Li Peng Wu Yan Zeng Chunchen Liu Zhi Geng CML 36 2 0 25 May 2024
An Invitation to Deep Reinforcement Learning Bernhard Jaeger Andreas Geiger OffRL OOD 80 5 0 13 Dec 2023
Exploiting Causality Signals in Medical Images: A Pilot Study with Empirical Results Gianluca Carloni Sara Colantonio 34 8 0 19 Sep 2023
Causal Parrots: Large Language Models May Talk Causality But Are Not Causal Matej Zečević Moritz Willig Devendra Singh Dhami Kristian Kersting LRM 30 102 0 24 Aug 2023
CausalOps -- Towards an Industrial Lifecycle for Causal Probabilistic Graphical Models R. Maier A. Schlattl Thomas Guess J. Mottok AI4CE 31 1 0 02 Aug 2023
Efficient Computation of Counterfactual Bounds Marco Zaffalon Alessandro Antonucci Rafael Cabañas David Huber Dario Azzimonti 21 2 0 17 Jul 2023
Conditionally Invariant Representation Learning for Disentangling Cellular Heterogeneity H. Aliee Ferdinand Kapl Soroor Hediyeh-zadeh Fabian J. Theis CML 31 6 0 02 Jul 2023
High Fidelity Image Counterfactuals with Probabilistic Causal Models Fabio De Sousa Ribeiro Tian Xia M. Monteiro Nick Pawlowski Ben Glocker DiffM 40 36 0 27 Jun 2023
Nonparametric Identifiability of Causal Representations from Unknown Interventions Julius von Kügelgen M. Besserve Wendong Liang Luigi Gresele Armin Kekić Elias Bareinboim David M. Blei Bernhard Schölkopf CML 23 57 0 01 Jun 2023
A Measure-Theoretic Axiomatisation of Causality Junhyung Park Simon Buchholz Bernhard Schölkopf Krikamol Muandet 40 5 0 19 May 2023
What's the Problem, Linda? The Conjunction Fallacy as a Fairness Problem Jose Alvarez Colmenares CML 26 0 0 16 May 2023
Dynamic Causal Explanation Based Diffusion-Variational Graph Neural Network for Spatio-temporal Forecasting G. Liang Prayag Tiwari Sławomir Nowaczyk Stefan Byttner F. Alonso-Fernandez DiffM 44 13 0 16 May 2023
CNNs with Multi-Level Attention for Domain Generalization Aristotelis Ballas Christos Diou OOD 29 6 0 02 Apr 2023
Optimal transport and Wasserstein distances for causal models Patrick Cheridito Stephan Eckstein OT 40 7 0 24 Mar 2023
Evaluating counterfactual explanations using Pearl's counterfactual method Bevan I. Smith CML 30 1 0 06 Jan 2023
Pearl Causal Hierarchy on Image Data: Intricacies & Challenges Matej Zečević Moritz Willig Devendra Singh Dhami Kristian Kersting 29 0 0 23 Dec 2022
Towards Cooperative Flight Control Using Visual-Attention Lianhao Yin Makram Chahine Tsun-Hsuan Wang Tim Seyde Chao Liu Mathias Lechner Ramin Hasani Daniela Rus 30 5 0 21 Dec 2022
Classifying text using machine learning models and determining conversation drift Chaitanya Chadha V. Gupta Deepak Gupta Ashish Khanna AILaw 29 2 0 15 Nov 2022
Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling Romain Lopez Natavsa Tagasovska Stephen Ra K. Cho J. Pritchard Aviv Regev OOD CML DRL 36 35 0 07 Nov 2022
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 41 11 0 07 Nov 2022
FL Games: A Federated Learning Framework for Distribution Shifts Sharut Gupta Kartik Ahuja Mohammad Havaei N. Chatterjee Yoshua Bengio OOD FedML 31 18 0 31 Oct 2022
Neural Attentive Circuits Nasim Rahaman M. Weiß Francesco Locatello C. Pal Yoshua Bengio Bernhard Schölkopf Erran L. Li Nicolas Ballas 32 6 0 14 Oct 2022
Distribution inference risks: Identifying and mitigating sources of leakage Valentin Hartmann Léo Meynent Maxime Peyrard Dimitrios Dimitriadis Shruti Tople Robert West MIACV 29 14 0 18 Sep 2022
On the Sparse DAG Structure Learning Based on Adaptive Lasso Danru Xu Erdun Gao Wei Huang Menghan Wang Andy Song Biwei Huang CML 32 4 0 07 Sep 2022
Data-Driven Causal Effect Estimation Based on Graphical Causal Modelling: A Survey Debo Cheng Jiuyong Li Lin Liu Jixue Liu T. Le CML 41 29 0 20 Aug 2022
Discovering Agents Zachary Kenton Ramana Kumar Sebastian Farquhar Jonathan G. Richens Matt MacDermott Tom Everitt CML 47 31 0 17 Aug 2022
Towards out of distribution generalization for problems in mechanics Lingxiao Yuan Harold S. Park Emma Lejeune OOD AI4CE 36 17 0 29 Jun 2022
Gated Domain Units for Multi-source Domain Generalization Simon Foll Alina Dubatovka Eugen Ernst Siu Lun Chau Martin Maritsch Patrik Okanovic Gudrun Thater J. M. Buhmann Felix Wortmann Krikamol Muandet OOD 43 4 0 24 Jun 2022
Using cognitive psychology to understand GPT-3 Marcel Binz Eric Schulz ELM LLMAG 254 447 0 21 Jun 2022
Towards a Solution to Bongard Problems: A Causal Approach Salahedine Youssef Matej Zečević Devendra Singh Dhami Kristian Kersting 35 5 0 14 Jun 2022
Analysis, Characterization, Prediction and Attribution of Extreme Atmospheric Events with Machine Learning: a Review S. Salcedo-Sanz Jorge Pérez-Aracil G. Ascenso Javier Del Ser D. Casillas-Pérez ... D. Barriopedro R. García-Herrera Marcello Restelli M. Giuliani A. Castelletti AI4Cl 25 13 0 03 Jun 2022
Amortized Inference for Causal Structure Learning Lars Lorch Scott Sussex Jonas Rothfuss Andreas Krause Bernhard Schölkopf CML 42 60 0 25 May 2022
Blackbird's language matrices (BLMs): a new benchmark to investigate disentangled generalisation in neural networks Paola Merlo A. An M. A. Rodriguez 38 9 0 22 May 2022
Active learning of causal probability trees Tue Herlau CML 20 0 0 17 May 2022
Machine Learning and Deep Learning -- A review for Ecologists Maximilian Pichler F. Hartig 47 127 0 11 Apr 2022
From Statistical to Causal Learning Bernhard Schölkopf Julius von Kügelgen CML 32 45 0 01 Apr 2022
Causality Inspired Representation Learning for Domain Generalization Fangrui Lv Jian Liang Shuang Li Bin Zang Chi Harold Liu Ziteng Wang Di Liu CML OOD 40 163 0 27 Mar 2022
Explainability in reinforcement learning: perspective and position Agneza Krajna Mario Brčič T. Lipić Juraj Dončević 34 27 0 22 Mar 2022
FaiRR: Faithful and Robust Deductive Reasoning over Natural Language Soumya Sanyal Harman Singh Xiang Ren ReLM LRM 32 45 0 19 Mar 2022
Evaluation Methods and Measures for Causal Learning Algorithms Lu Cheng Ruocheng Guo Raha Moraffah Paras Sheth K. S. Candan Huan Liu CML ELM 29 51 0 07 Feb 2022
A Causal Lens for Controllable Text Generation Zhiting Hu Erran L. Li 45 59 0 22 Jan 2022
Causal Discovery from Sparse Time-Series Data Using Echo State Network Haonan Chen B. Chang Mohamed A. Naiel1 Georges Younes Steven Wardell Stan Kleinikkink J. S. Z. U. O. Waterloo CML BDL AI4TS 24 1 0 09 Jan 2022
Encoding Causal Macrovariables Benedikt Höltgen CML 21 3 0 29 Nov 2021