Papers
Evaluating Humanlike Memory Effects in Transformers Using Item Recognition Tasks
Christian Clark, William Schuler
Differentiable Causal Search
Kaveh Aryan, Hana Chockler, Mohammad Reza Mousavi
Information-Theoretic Causal Bounds under Unmeasured Confounding
Yonghan Jung, Bogyeong Kang
Causal and Active Learning-Based Counterfactual Chest X-ray Generation for Supporting Clinical Decision-Making in Lung Disease
Yifei Zhu, Greta Mohr, Lei Zhang et al.
Proxy-Guided Measurement Calibration
Saketh Vishnubhatla, Shu Wan, Andre Harrison et al.
Sharp Bounds for Treatment Effect Generalization under Outcome Distribution Shift
Amir Asiaee, Samhita Pal, Cole Beck et al.
Causal Discovery in Action: Learning Chain-Reaction Mechanisms from Interventions
Panayiotis Panayiotou, Özgür Şimşek
Bayesian Causal Discovery Networks for Linear Mixed Data
Moabi Mokhoro, Ioan Gabriel Bucur, Tom Heskes et al.
Intervening to learn and compose causally disentangled representations
Alex Markham, Isaac Hirsch, Jeri A. Chang et al.
Causal Process Models: Reframing Dynamic Causal Graph Discovery as a Reinforcement Learning Problem
Turan Orujlu, Christian Gumbsch, Martin V. Butz et al.
Causal Discovery for Efficient Offline RL with Factored Action Spaces
Cecilia Ehrlichman, Michael Dykstra, Shengpu Tang et al.
Estimation and Inference for Causal Explainability
Weihan Zhang, Zijun Gao
Debiased Machine Learning for Conformal Prediction of Counterfactual Outcomes Under Runtime Confounding
Keith Barnatchez, Kevin P. Josey, Rachel C. Nethery et al.
Coarsening Causal DAG Models
Francisco Madaleno, Pratik Misra, Alex Markham
IV Co-Scientist: Multi-Agent LLM Framework for Causal Instrumental Variable Discovery
Ivaxi Sheth, Zhijing Jin, Bryan Wilder et al.
Domain Faithfulness through Counterfactually Robust Learning
Ananth Balashankar, Ankit Bhardwaj, Neelabh Madan et al.
The Generalised Kernel Covariance Measure
Luca Bergen, Dino Sejdinovic, Vanessa Didelez
Nonparametric Greedy Equivalence Search with Prior-Fitted Networks
Mateusz Gajewski, Mateusz Olko
Causal Foundations of Collective Agency
Frederik Hytting Jørgensen, Sebastian Weichwald, Lewis Hammond
Information-theoretic signatures of causality in Bayesian networks and hypergraphs
Sung En Chiang, Zhaolu Liu, Robert Peach et al.
Bivariate Causal Discovery Using Rate-Distortion MDL: An Information Dimension Approach
Tiago Brogueira, Mario A. T. Figueiredo
Cost-Aware Optimized Front-Door Experimental Design
Leopold Mareis, Mathias Drton
Causal Articulation Theory (CAT): Articulating Static and Temporal Causal Models Beyond LLM Rationalizations
Matej Zečević, Devendra Singh Dhami, Kristian Kersting
A causal machine learning framework for pharmacovigilance signal detection in electronic health records: Drug-induced acute kidney injury
Stella Dimitsaki, Corinne Isnard Bagnis, Pantelis Natsiavas et al.