Wang Miao: Introducing the specificity score: a measure of causality beyond P value

Rodrigo Pinto: What is causality? How to express it? And why it matters

Abhin Shah: On counterfactual inference with unobserved confounding via exponential family

Brian Gilbert: Identification/estimation of mediation effects of longitudinal modified policies

Raaz Dwivedi: Integrating Double Robustness into Causal Latent Factor Models

Hyunseung Kang: Transfer Learning Between U.S. Presidential Elections

Andrew Yiu: Semiparametric posterior corrections

Chan Park: Single Proxy Control

Mihaela van der Schaar: The (Causal) Discovery Ladder: Unravelling Governing Equations and Beyond

Kosuke Imai: The Cram Method for Efficient Simultaneous Learning and Evaluation

Krikamol Muandet: A Measure-Theoretic Axiomatisation of Causality

Sara Magliacane & Phillip Lippe: BISCUIT: Causal Representation Learning from Binary Interactions

David Lagnado: Causality in Mind: Learning, Reasoning and Blaming

Maria Glymour: Evidence triangulation in dementia research

Giulio Grossi: SMaC: Spatial Matrix Completion method

Xinwei Shen: Causality-oriented robustness: exploiting data heterogeneity at different levels

Iván Díaz: Recanting twins: addressing intermediate confounding in mediation analysis

Ting Ye: Debiased Multivariable Mendelian Randomization

Fan Yang: Mediation analysis with the mediator and outcome missing not at random

Victor Veitch: Linear Structure of (Causal) Concepts in Generative AI

Jonas Peters, Nicola Gnecco, Sorawit Saengkyongam: Invariance-based Generalization and Extrapolation

Elizabeth Tipton: Designing Randomized Trials to Predict Treatment Effects

Mats Stensrud & Aaron Sarvet: Interpretational errors in causal inference and how to avoid them

Erica Moodie: Flexible modeling of adaptive treatment strategies for censored outcomes

Yuqi Gu: Identifiable Deep Generative Models for Rich Data Types with Discrete Latent Layers

Maya Mathur: A common-cause principle for eliminating selection bias in causal estimands

Anish Agarwal: On Causal Inference with Temporal and Spatial Spillovers in Panel Data

Richard Guo: Confounder selection via iterative graph expansion

Chris Harshaw: ClipOGD: Experimental Design for Adaptive Neyman Allocation in Sequential Experiments

Michael Celentano: Challenges of the inconsistency regime: Novel debiasing methods for missing data