On the Number of Experiments Sufficient and in the Worst Case Necessary to Identify All Causal Relations Among N Variables. - Frederick Eberhardt; Clark Glymour; Richard Scheines (UAI, 2005)

Compact Similarity Joins. - Brent Bryan; Frederick Eberhardt; Christos Faloutsos (ICDE, 2008)

Almost Optimal Intervention Sets for Causal Discovery. - Frederick Eberhardt (UAI, 2008)

A sufficient condition for pooling data. - Frederick Eberhardt (Synth., 2008)

Causal Discovery as a Game. - Frederick Eberhardt (NIPS Causality: Objectives and Assessment, 2010)

Combining Experiments to Discover Linear Cyclic Models with Latent Variables. - Frederick Eberhardt; Patrik O. Hoyer; Richard Scheines (AISTATS, 2010)

Actual causation: a stone soup essay. - Clark Glymour; David Danks; Bruce Glymour; Frederick Eberhardt; Joseph D. Ramsey; Richard Scheines; Peter Spirtes; Choh Man Teng 001; Jiji Zhang (Synth., 2010)

Noisy-OR Models with Latent Confounding. - Antti Hyttinen; Frederick Eberhardt; Patrik O. Hoyer (UAI, 2011)

Confirmation in the Cognitive Sciences: The Problematic Case of Bayesian Models. - Frederick Eberhardt; David Danks (Minds Mach., 2011)

Reliability via synthetic a priori: Reichenbach's doctoral thesis on probability. - Frederick Eberhardt (Synth., 2011)

Hans Reichenbach's Probability Logic. - Frederick Eberhardt; Clark Glymour (Inductive Logic, 2011)

Causal Discovery of Linear Cyclic Models from Multiple Experimental Data Sets with Overlapping Variables. - Antti Hyttinen; Frederick Eberhardt; Patrik O. Hoyer (UAI, 2012)

Learning linear cyclic causal models with latent variables. - Antti Hyttinen; Frederick Eberhardt; Patrik O. Hoyer (J. Mach. Learn. Res., 2012)

Discovering Cyclic Causal Models with Latent Variables: A General SAT-Based Procedure. - Antti Hyttinen; Patrik O. Hoyer; Frederick Eberhardt; Matti Järvisalo (UAI, 2013)

Experiment selection for causal discovery. - Antti Hyttinen; Frederick Eberhardt; Patrik O. Hoyer (J. Mach. Learn. Res., 2013)

Constraint-based Causal Discovery: Conflict Resolution with Answer Set Programming. - Antti Hyttinen; Frederick Eberhardt; Matti Järvisalo (UAI, 2014)

Visual Causal Feature Learning. - Krzysztof Chalupka; Pietro Perona; Frederick Eberhardt (UAI, 2015)

Do-calculus when the True Graph Is Unknown. - Antti Hyttinen; Frederick Eberhardt; Matti Järvisalo (UAI, 2015)

Multi-Level Cause-Effect Systems. - Krzysztof Chalupka; Frederick Eberhardt; Pietro Perona (AISTATS, 2016)

Causal Discovery from Subsampled Time Series Data by Constraint Optimization. - Antti Hyttinen; Sergey M. Plis; Matti Järvisalo; Frederick Eberhardt; David Danks (Probabilistic Graphical Models, 2016)

Unsupervised Discovery of El Nino Using Causal Feature Learning on Microlevel Climate Data. - Krzysztof Chalupka; Tobias Bischoff; Frederick Eberhardt; Pietro Perona (UAI, 2016)

Estimating Causal Direction and Confounding of Two Discrete Variables. - Krzysztof Chalupka; Frederick Eberhardt; Pietro Perona (CoRR, 2016)

Green and grue causal variables. - Frederick Eberhardt (Synth., 2016)

SAT-Based Causal Discovery under Weaker Assumptions. - Zhalama; Jiji Zhang; Frederick Eberhardt; Wolfgang Mayer (UAI, 2017)

A constraint optimization approach to causal discovery from subsampled time series data. - Antti Hyttinen; Sergey M. Plis; Matti Järvisalo; Frederick Eberhardt; David Danks (Int. J. Approx. Reason., 2017)

Introduction to the foundations of causal discovery. - Frederick Eberhardt (Int. J. Data Sci. Anal., 2017)

Fast Conditional Independence Test for Vector Variables with Large Sample Sizes. - Krzysztof Chalupka; Pietro Perona; Frederick Eberhardt (CoRR, 2018)

Beyond Cause-Effect Pairs. - Frederick Eberhardt (Cause Effect Pairs in Machine Learning, 2019)

ASP-based Discovery of Semi-Markovian Causal Models under Weaker Assumptions. - Zhalama; Jiji Zhang; Frederick Eberhardt; Wolfgang Mayer; Mark Junjie Li (IJCAI, 2019)

Approximate Causal Abstractions. - Sander Beckers; Frederick Eberhardt; Joseph Y. Halpern (UAI, 2019)

Approximate Causal Abstraction. - Sander Beckers; Frederick Eberhardt; Joseph Y. Halpern (CoRR, 2019)

Controlling for discrete unmeasured confounding in nonlinear causal models. - Patrick Burauel; Frederick Eberhardt; Michel Besserve (CLeaR, 2025)

Lower Bounds on the Size of Markov Equivalence Classes. - Erik Jahn; Frederick Eberhardt; Leonard J. Schulman (UAI, 2025)

Discovering Causal Models with Optimization: Confounders, Cycles, and Instrument Validity. - Frederick Eberhardt; Nur Kaynar; Auyon Siddiq (Manag. Sci., 2025)

Modeling Discrimination with Causal Abstraction. - Milan Mossé; Kara Schechtman; Frederick Eberhardt; Thomas Icard (CoRR, 2025)