CLeaR 2022

48 papers

Some Reflections on Drawing Causal Inference using Textual Data: Parallels Between Human Subjects and Organized Texts

Bo Zhang, Jiayao Zhang

Can Humans Be out of the Loop?

Junzhe Zhang, Elias Bareinboim

Causal Discovery for Linear Mixed Data

Yan Zeng, Shohei Shimizu, Hidetoshi Matsui, Fuchun Sun

Causal Discovery in Linear Structural Causal Models with Deterministic Relations

Yuqin Yang, Mohamed S Nafea, AmirEmad Ghassami, Negar Kiyavash

Fair Classification with Instance-dependent Label Noise

Songhua Wu, Mingming Gong, Bo Han, Yang Liu, Tongliang Liu

Integrative R-learner of heterogeneous treatment effects combining experimental and observational studies

Lili Wu, Shu Yang

Identifying Coarse-grained Independent Causal Mechanisms with Self-supervision

Xiaoyang Wang, Klara Nahrstedt, Oluwasanmi O Koyejo

A Uniformly Consistent Estimator of non-Gaussian Causal Effects Under the k-Triangle-Faithfulness Assumption

Shuyan Wang, Peter Spirtes

Local Constraint-Based Causal Discovery under Selection Bias

Philip Versteeg, Joris Mooij, Cheng Zhang

A Multivariate Causal Discovery based on Post-Nonlinear Model

Kento Uemura, Takuya Takagi, Kambayashi Takayuki, Hiroyuki Yoshida, Shohei Shimizu

Same Cause; Different Effects in the Brain

Mariya Toneva, Jennifer Williams, Anand Bollu, Christoph Dann, Leila Wehbe

Attainability and Optimality: The Equalized Odds Fairness Revisited

Zeyu Tang, Kun Zhang

Identifying Principal Stratum Causal Effects Conditional on a Post-treatment Intermediate Response

Xiaoqing Tan, Judah Abberbock, Priya Rastogi, Gong Tang

Estimating Social Influence from Observational Data

Dhanya Sridhar, Caterina De Bacco, David Blei

Causal Imputation via Synthetic Interventions

Chandler Squires, Dennis Shen, Anish Agarwal, Devavrat Shah, Caroline Uhler

Causal Structure Discovery between Clusters of Nodes Induced by Latent Factors

Chandler Squires, Annie Yun, Eshaan Nichani, Raj Agrawal, Caroline Uhler

Diffusion Causal Models for Counterfactual Estimation

Pedro Sanchez, Sotirios A. Tsaftaris

On the Equivalence of Causal Models: A Category-Theoretic Approach

Jun Otsuka, Hayato Saigo

Differentially Private Estimation of Heterogeneous Causal Effects

Fengshi Niu, Harsha Nori, Brian Quistorff, Rich Caruana, Donald Ngwe

Optimal Training of Fair Predictive Models

Razieh Nabi, Daniel Malinsky, Ilya Shpitser

Equality Constraints in Linear Hawkes Processes

Søren Wengel Mogensen

CausalCity: Complex Simulations with Agency for Causal Discovery and Reasoning

Daniel McDuff, Yale Song, Jiyoung Lee, Vibhav Vineet, Sai Vemprala

A Distance Covariance-based Kernel for Nonlinear Causal Clustering in Heterogeneous Populations

Alex Markham, Richeek Das, Moritz Grosse-wentrup

Efficient Reinforcement Learning with Prior Causal Knowledge

Yangyi Lu, Amirhossein Meisami, Ambuj Tewari

Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data

Sindy Löwe, David Madras, Richard Zemel, Max Welling

Data-driven exclusion criteria for instrumental variable studies

Tony Liu, Patrick Lawlor, Lyle Ungar, Konrad Kording

Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA

Sébastien Lachapelle, Pau Rodriguez, Yash Sharma, Katie E Everett, Rémi Le Priol

Causal Bandits without prior knowledge using separating sets

Arnoud De Kroon, Joris Mooij, Danielle Belgrave

Learning Causal Overhypotheses through Exploration in Children and Computational Models

Eliza Kosoy, Adrian Liu, Jasmine L Collins, David Chan, Jessica B Hamrick

Non-parametric Inference Adaptive to Intrinsic Dimension

Khashayar Khosravi, Greg Lewis, Vasilis Syrgkanis

Predictive State Propensity Subclassification (PSPS): A causal inference algorithm for data-driven propensity score stratification

Joseph Kelly, Jing Kong, Georg M. Goerg

Simple data balancing achieves competitive worst-group-accuracy

Badr Youbi Idrissi, Martin Arjovsky, Mohammad Pezeshki, David Lopez-paz

Partial Identification with Noisy Covariates: A Robust Optimization Approach

Wenshuo Guo, Mingzhang Yin, Yixin Wang, Michael Jordan

Info Intervention and its Causal Calculus

Heyang Gong, Ke Zhu

Learning Invariant Representations with Missing Data

Mark Goldstein, Joern-Henrik Jacobsen, Olina Chau, Adriel Saporta, Aahlad Manas Puli

Selection, Ignorability and Challenges With Causal Fairness

Jake Fawkes, Robin Evans, Dino Sejdinovic

Differentiable Causal Discovery Under Latent Interventions

Gonçalo Rui Alves Faria, Andre Martins, Mario A. T. Figueiredo

Bivariate Causal Discovery via Conditional Divergence

Bao Duong, Thin Nguyen

Interactive rank testing by betting

Boyan Duan, Aaditya Ramdas, Larry Wasserman

Disentangling Controlled Effects for Hierarchical Reinforcement Learning

Oriol Corcoll, Raul Vicente

Typing assumptions improve identification in causal discovery

Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin

Process Independence Testing in Proximal Graphical Event Models

Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Dharmashankar Subramanian

Cause-effect inference through spectral independence in linear dynamical systems: theoretical foundations

Michel Besserve, Naji Shajarisales, Dominik Janzing, Bernhard Schölkopf

Causal Explanations and XAI

Sander Beckers

VIM: Variational Independent Modules for Video Prediction

Rim Assouel, Lluis Castrejon, Aaron Courville, Nicolas Ballas, Yoshua Bengio

Weakly Supervised Discovery of Semantic Attributes

Ameen Ali Ali, Tomer Galanti, Evgenii Zheltonozhskii, Chaim Baskin, Lior Wolf

Towards efficient representation identification in supervised learning

Kartik Ahuja, Divyat Mahajan, Vasilis Syrgkanis, Ioannis Mitliagkas

Relational Causal Models with Cycles: Representation and Reasoning

Ragib Ahsan, David Arbour, Elena Zheleva