Thomas S. Richardson

55 papers A* 1A 21Journal 28Unranked 2

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	A Nonparametric Bayes Approach to Online Activity Prediction. CoRR Mario Beraha, Lorenzo Masoero, Stefano Favaro, Thomas S. Richardson
2024	J	`jnl`	Assumptions and Bounds in the Instrumental Variable Model. CoRR Thomas S. Richardson, James M. Robins
2024	J	`jnl`	Improved prediction of future user activity in online A/B testing. CoRR Lorenzo Masoero, Mario Beraha, Thomas S. Richardson, Stefano Favaro
2022	A	`conf`	A Bayesian Model for Online Activity Sample Sizes. AISTATS Thomas S. Richardson, Yu Liu, James McQueen, Doug Hains
2022	—	`ch.`	An Interventionist Approach to Mediation Analysis. Probabilistic and Causal Inference James M. Robins, Thomas S. Richardson, Ilya Shpitser
2022	—	`ch.`	Multivariate Counterfactual Systems and Causal Graphical Models. Probabilistic and Causal Inference Ilya Shpitser, Thomas S. Richardson, James M. Robins
2022	J	`jnl`	The m-connecting imset and factorization for ADMG models. CoRR Bryan Andrews, Gregory F. Cooper, Thomas S. Richardson, Peter Spirtes
2021	J	`jnl`	Bayesian Sample Size Prediction for Online Activity. CoRR Thomas S. Richardson, Yu Liu, James McQueen, Doug Hains
2021	J	`jnl`	Chernoff-Type Concentration of Empirical Probabilities in Relative Entropy. IEEE Trans. Inf. Theory F. Richard Guo, Thomas S. Richardson
2021	J	`jnl`	Multiple Randomization Designs. CoRR Patrick Bajari, Brian Burdick, Guido W. Imbens, Lorenzo Masoero, James McQueen, Thomas S. Richardson, Ido M. Rosen
2019	A	`conf`	A Potential Outcomes Calculus for Identifying Conditional Path-Specific Effects. AISTATS Daniel Malinsky, Ilya Shpitser, Thomas S. Richardson
2018	A	`conf`	Acyclic Linear SEMs Obey the Nested Markov Property. UAI Ilya Shpitser, Robin J. Evans, Thomas S. Richardson
2015	A	`conf`	A Finite Population Likelihood Ratio Test of the Sharp Null Hypothesis for Compliers. UAI Wen Wei Loh, Thomas S. Richardson
2014	J	`jnl`	A factorization criterion for acyclic directed mixed graphs. CoRR Thomas S. Richardson
2014	J	`jnl`	Variations on undirected graphical models and their relationships. Kybernetika David Heckerman, Christopher Meek, Thomas S. Richardson
2013	J	`jnl`	A Discovery Algorithm for Directed Cyclic Graphs CoRR Thomas S. Richardson
2013	J	`jnl`	A Polynomial-Time Algorithm for Deciding Markov Equivalence of Directed Cyclic Graphical Models CoRR Thomas S. Richardson
2013	J	`jnl`	Causal Inference in the Presence of Latent Variables and Selection Bias CoRR Peter Spirtes, Christopher Meek, Thomas S. Richardson
2013	J	`jnl`	Cross-covariance modelling via DAGs with hidden variables CoRR Jacob A. Wegelin, Thomas S. Richardson
2013	J	`jnl`	Markov Equivalence Classes for Maximal Ancestral Graphs CoRR Ayesha R. Ali, Thomas S. Richardson
2013	A	`conf`	Sparse Nested Markov models with Log-linear Parameters. UAI Ilya Shpitser, Robin J. Evans, Thomas S. Richardson, James M. Robins
2013	J	`jnl`	Sparse Nested Markov models with Log-linear Parameters. CoRR Ilya Shpitser, Robin J. Evans, Thomas S. Richardson, James M. Robins
2012	J	`jnl`	A New Algorithm for Maximum Likelihood Estimation in Gaussian Graphical Models for Marginal Independence CoRR Mathias Drton, Thomas S. Richardson
2012	J	`jnl`	An Efficient Algorithm for Computing Interventional Distributions in Latent Variable Causal Models CoRR Ilya Shpitser, Thomas S. Richardson, James M. Robins
2012	J	`jnl`	Iterative Conditional Fitting for Gaussian Ancestral Graph Models CoRR Mathias Drton, Thomas S. Richardson
2012	J	`jnl`	Maximum likelihood fitting of acyclic directed mixed graphs to binary data CoRR Robin J. Evans, Thomas S. Richardson
2012	A	`conf`	Nested Markov Properties for Acyclic Directed Mixed Graphs. UAI Thomas S. Richardson, James M. Robins, Ilya Shpitser
2012	J	`jnl`	Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (2006) CoRR Rina Dechter, Thomas S. Richardson
2012	J	`jnl`	Towards Characterizing Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables CoRR Ayesha R. Ali, Thomas S. Richardson, Peter Spirtes, Jiji Zhang
2012	J	`jnl`	Using the structure of d-connecting paths as a qualitative measure of the strength of dependence CoRR Sanjay Chaudhari, Thomas S. Richardson
2011	A	`conf`	An Efficient Algorithm for Computing Interventional Distributions in Latent Variable Causal Models. UAI Ilya Shpitser, Thomas S. Richardson, James M. Robins
2011	J	`jnl`	Learning high-dimensional DAGs with latent and selection variables CoRR Diego Colombo, Marloes H. Maathuis, Markus Kalisch, Thomas S. Richardson
2011	A	`conf`	Learning high-dimensional DAGs with latent and selection variables (Abstract). UAI Diego Colombo, Marloes H. Maathuis, Markus Kalisch, Thomas S. Richardson
2010	A	`conf`	Maximum likelihood fitting of acyclic directed mixed graphs to binary data. UAI Robin J. Evans, Thomas S. Richardson
2010	J	`jnl`	Rescuing Loading Induced Bone Formation at Senescence. PLoS Comput. Biol. Sundar Srinivasan, Brandon J. Ausk, Jitendra Prasad, Dewayne Threet, Steven D. Bain, Thomas S. Richardson, Ted S. Gross
2009	A	`conf`	A factorization criterion for acyclic directed mixed graphs. UAI Thomas S. Richardson
2009	J	`jnl`	Computing Maximum Likelihood Estimates in Recursive Linear Models with Correlated Errors. J. Mach. Learn. Res. Mathias Drton, Michael Eichler, Thomas S. Richardson
2009	A*	`conf`	Testing Edges by Truncations. IJCAI Ilya Shpitser, Thomas S. Richardson, James M. Robins
2008	J	`jnl`	Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models. J. Mach. Learn. Res. Mathias Drton, Thomas S. Richardson
2005	A	`conf`	Towards Characterizing Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables. UAI Ayesha R. Ali, Thomas S. Richardson, Peter Spirtes, Jiji Zhang
2004	A	`conf`	Iterative Conditional Fitting for Gaussian Ancestral Graph Models. UAI Mathias Drton, Thomas S. Richardson
2003	A	`conf`	A New Algorithm for Maximum Likelihood Estimation in Gaussian Graphical Models for Marginal Independence. UAI Mathias Drton, Thomas S. Richardson
2003	—	`conf`	Continuation based control of aircraft dynamics. CDC Thomas S. Richardson, Guy A. Charles, David P. Stoten, Mario di Bernardo, Mark H. Lowenberg
2002	—	`conf`	Evaluation of Sequential Importance Sampling for blind deconvolution via a simulation study. EUSIPCO Ali R. Ayesha, Alejandro Murua, Thomas S. Richardson, Roy Sumit
2002	A	`conf`	Markov Equivalence Classes for Maximal Ancestral Graphs. UAI Ayesha R. Ali, Thomas S. Richardson
2001	A	`conf`	Cross-covariance modelling via DAGs with hidden variables. UAI Jacob A. Wegelin, Thomas S. Richardson
2001	A	`ed.`	Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, AISTATS 2001, Key West, Florida, USA, January 4-7, 2001 AISTATS Thomas S. Richardson, Tommi S. Jaakkola
2000	J	`jnl`	Guest editorial. Stat. Comput. Thomas S. Richardson
1998	—	`ch.`	Chain Graphs and Symmetric Associations. Learning in Graphical Models Thomas S. Richardson
1997	A	`conf`	A Note on Cyclic Graphs and Dynamical Feedback Systems. AISTATS Thomas S. Richardson, Peter Spirtes, Clark Glymour
1997	A	`conf`	A Polynomial Time Algorithm for Determining DAG Equivalence in the Presence of Latent Variables and Selection Bias. AISTATS Peter Spirtes, Thomas S. Richardson
1997	J	`jnl`	An evaluation of machine-learning methods for predicting pneumonia mortality. Artif. Intell. Medicine Gregory F. Cooper, Constantin F. Aliferis, Richard Ambrosino, John M. Aronis, Bruce G. Buchanan, Rich Caruana, Michael J. Fine, Clark Glymour, Geoffrey J. Gordon, Barbara H. Hanusa, Janine E. Janosky, Christopher Meek, Tom M. Mitchell, Thomas S. Richardson, Peter Spirtes
1997	A	`conf`	Extensions of Undirected and Acyclic, Directed Graphical Models. AISTATS Thomas S. Richardson
1997	A	`conf`	Heuristic Greedy Search Algorithms for Latent Variable Models. AISTATS Peter Spirtes, Thomas S. Richardson, Christopher Meek
1995	A	`conf`	Causal Inference in the Presence of Latent Variables and Selection Bias. UAI Peter Spirtes, Christopher Meek, Thomas S. Richardson