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Thomas Richardson 0001
Person information
- affiliation: University of Washington, Statistics Department, WA, USA
- affiliation: Carnegie Mellon University, Department of Philosophy, Pittsburgh, USA
Other persons with the same name
- Thomas Richardson — disambiguation page
- Tom Richardson 0002
(aka: Thomas Richardson 0002, Thomas S. Richardson 0002) — University of Bristol, Department of Aerospace Engineering, UK
- Thomas Richardson 0003 — University of York, UK
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2020 – today
- 2024
- [i22]Thomas S. Richardson, James M. Robins:
Assumptions and Bounds in the Instrumental Variable Model. CoRR abs/2401.13758 (2024) - [i21]Mario Beraha, Lorenzo Masoero, Stefano Favaro, Thomas S. Richardson:
A Nonparametric Bayes Approach to Online Activity Prediction. CoRR abs/2401.14722 (2024) - [i20]Lorenzo Masoero, Mario Beraha, Thomas S. Richardson, Stefano Favaro:
Improved prediction of future user activity in online A/B testing. CoRR abs/2402.03231 (2024) - 2022
- [c31]Thomas S. Richardson, Yu Liu, James McQueen, Doug Hains:
A Bayesian Model for Online Activity Sample Sizes. AISTATS 2022: 1775-1785 - [p3]James M. Robins, Thomas S. Richardson, Ilya Shpitser:
An Interventionist Approach to Mediation Analysis. Probabilistic and Causal Inference 2022: 713-764 - [p2]Ilya Shpitser, Thomas S. Richardson, James M. Robins:
Multivariate Counterfactual Systems and Causal Graphical Models. Probabilistic and Causal Inference 2022: 813-852 - [i19]Bryan Andrews, Gregory F. Cooper, Thomas S. Richardson, Peter Spirtes:
The m-connecting imset and factorization for ADMG models. CoRR abs/2207.08963 (2022) - 2021
- [j10]F. Richard Guo
Chernoff-Type Concentration of Empirical Probabilities in Relative Entropy. IEEE Trans. Inf. Theory 67(1): 549-558 (2021) - [i18]Thomas S. Richardson, Yu Liu, James McQueen, Doug Hains:
Bayesian Sample Size Prediction for Online Activity. CoRR abs/2111.12157 (2021) - [i17]Patrick Bajari, Brian Burdick, Guido W. Imbens, Lorenzo Masoero, James McQueen, Thomas S. Richardson, Ido M. Rosen:
Multiple Randomization Designs. CoRR abs/2112.13495 (2021)
2010 – 2019
- 2019
- [c30]Daniel Malinsky, Ilya Shpitser, Thomas S. Richardson:
A Potential Outcomes Calculus for Identifying Conditional Path-Specific Effects. AISTATS 2019: 3080-3088 - 2018
- [c29]Ilya Shpitser, Robin J. Evans, Thomas S. Richardson:
Acyclic Linear SEMs Obey the Nested Markov Property. UAI 2018: 735-745 - 2015
- [c28]Wen Wei Loh
A Finite Population Likelihood Ratio Test of the Sharp Null Hypothesis for Compliers. UAI 2015: 523-532 - 2014
- [j9]David Heckerman, Christopher Meek, Thomas S. Richardson:
Variations on undirected graphical models and their relationships. Kybernetika 50(3): 363-377 (2014) - [i16]Thomas S. Richardson:
A factorization criterion for acyclic directed mixed graphs. CoRR abs/1406.6764 (2014) - 2013
- [j8]Ciprian Chelba, Peng Xu, Fernando Pereira, Thomas Richardson:
Large Scale Distributed Acoustic Modeling With Back-Off ℕ-Grams. IEEE Trans. Speech Audio Process. 21(6): 1158-1169 (2013) - [c27]Ilya Shpitser, Robin J. Evans, Thomas S. Richardson, James M. Robins:
Sparse Nested Markov models with Log-linear Parameters. UAI 2013 - [i15]Ayesha R. Ali, Thomas S. Richardson:
Markov Equivalence Classes for Maximal Ancestral Graphs. CoRR abs/1301.0550 (2013) - [i14]Jacob A. Wegelin, Thomas S. Richardson:
Cross-covariance modelling via DAGs with hidden variables. CoRR abs/1301.2316 (2013) - [i13]Ciprian Chelba, Peng Xu, Fernando Pereira, Thomas Richardson:
Large Scale Distributed Acoustic Modeling With Back-off N-grams. CoRR abs/1302.1123 (2013) - [i12]Thomas S. Richardson:
A Discovery Algorithm for Directed Cyclic Graphs. CoRR abs/1302.3599 (2013) - [i11]Thomas S. Richardson:
A Polynomial-Time Algorithm for Deciding Markov Equivalence of Directed Cyclic Graphical Models. CoRR abs/1302.3600 (2013) - [i10]Peter Spirtes, Christopher Meek, Thomas S. Richardson:
Causal Inference in the Presence of Latent Variables and Selection Bias. CoRR abs/1302.4983 (2013) - [i9]Ilya Shpitser, Robin J. Evans, Thomas S. Richardson, James M. Robins:
Sparse Nested Markov models with Log-linear Parameters. CoRR abs/1309.6863 (2013) - 2012
- [c26]Ciprian Chelba, Peng Xu, Fernando Pereira, Thomas Richardson:
Distributed acoustic modeling with back-off n-grams. ICASSP 2012: 4129-4132 - [c25]Thomas S. Richardson, James M. Robins, Ilya Shpitser:
Nested Markov Properties for Acyclic Directed Mixed Graphs. UAI 2012: 13 - [i8]Ilya Shpitser, Thomas S. Richardson, James M. Robins:
An Efficient Algorithm for Computing Interventional Distributions in Latent Variable Causal Models. CoRR abs/1202.3763 (2012) - [i7]Robin J. Evans, Thomas S. Richardson:
Maximum likelihood fitting of acyclic directed mixed graphs to binary data. CoRR abs/1203.3479 (2012) - [i6]Ayesha R. Ali, Thomas S. Richardson, Peter Spirtes, Jiji Zhang:
Towards Characterizing Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables. CoRR abs/1207.1365 (2012) - [i5]Mathias Drton, Thomas S. Richardson:
Iterative Conditional Fitting for Gaussian Ancestral Graph Models. CoRR abs/1207.4118 (2012) - [i4]Rina Dechter, Thomas S. Richardson:
Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (2006). CoRR abs/1208.5160 (2012) - [i3]Mathias Drton, Thomas S. Richardson:
A New Algorithm for Maximum Likelihood Estimation in Gaussian Graphical Models for Marginal Independence. CoRR abs/1212.2462 (2012) - [i2]Sanjay Chaudhari, Thomas S. Richardson:
Using the structure of d-connecting paths as a qualitative measure of the strength of dependence. CoRR abs/1212.2469 (2012) - 2011
- [c24]Ilya Shpitser, Thomas S. Richardson, James M. Robins:
An Efficient Algorithm for Computing Interventional Distributions in Latent Variable Causal Models. UAI 2011: 661-670 - [c23]Diego Colombo, Marloes H. Maathuis, Markus Kalisch, Thomas S. Richardson:
Learning high-dimensional DAGs with latent and selection variables (Abstract). UAI 2011: 850 - [i1]Diego Colombo, Marloes H. Maathuis
Learning high-dimensional DAGs with latent and selection variables. CoRR abs/1104.5617 (2011) - 2010
- [j7]Sundar Srinivasan, Brandon J. Ausk, Jitendra Prasad
Rescuing Loading Induced Bone Formation at Senescence. PLoS Comput. Biol. 6(9) (2010) - [c22]Robin J. Evans, Thomas S. Richardson:
Maximum likelihood fitting of acyclic directed mixed graphs to binary data. UAI 2010: 177-184
2000 – 2009
- 2009
- [j6]Mathias Drton, Michael Eichler, Thomas S. Richardson:
Computing Maximum Likelihood Estimates in Recursive Linear Models with Correlated Errors. J. Mach. Learn. Res. 10: 2329-2348 (2009) - [c21]Ilya Shpitser, Thomas S. Richardson, James M. Robins:
Testing Edges by Truncations. IJCAI 2009: 1957-1963 - [c20]Thomas S. Richardson:
A factorization criterion for acyclic directed mixed graphs. UAI 2009: 462-470 - 2008
- [j5]Mathias Drton, Thomas S. Richardson:
Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models. J. Mach. Learn. Res. 9: 893-914 (2008) - 2005
- [c19]Ayesha R. Ali, Thomas S. Richardson, Peter Spirtes, Jiji Zhang:
Towards Characterizing Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables. UAI 2005: 10-17 - 2004
- [c18]Mathias Drton, Thomas S. Richardson:
Iterative Conditional Fitting for Gaussian Ancestral Graph Models. UAI 2004: 130-137 - 2003
- [c17]Thomas S. Richardson, Guy A. Charles, David P. Stoten, Mario di Bernardo, Mark H. Lowenberg
Continuation based control of aircraft dynamics. CDC 2003: 4932-4938 - [c16]Sanjay Chaudhuri, Thomas Richardson:
Using the structure of d-connecting paths as a qualitative measure of the strength of dependence. UAI 2003: 116-123 - [c15]Mathias Drton, Thomas S. Richardson:
A New Algorithm for Maximum Likelihood Estimation in Gaussian Graphical Models for Marginal Independence. UAI 2003: 184-191 - 2002
- [c14]Ali R. Ayesha, Alejandro Murua, Thomas S. Richardson, Roy Sumit:
Evaluation of Sequential Importance Sampling for blind deconvolution via a simulation study. EUSIPCO 2002: 1-4 - [c13]Geoffrey Zweig, Jeff A. Bilmes, Thomas Richardson, Karim Filali, Karen Livescu
Structurally discriminative graphical models for automatic speech recognition - results from the 2001 Johns Hopkins Summer Workshop. ICASSP 2002: 93-96 - [c12]Ayesha R. Ali, Thomas S. Richardson:
Markov Equivalence Classes for Maximal Ancestral Graphs. UAI 2002: 1-9 - 2001
- [c11]Jacob A. Wegelin, Thomas S. Richardson:
Cross-covariance modelling via DAGs with hidden variables. UAI 2001: 546-553 - [e1]Thomas S. Richardson, Tommi S. Jaakkola:
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, AISTATS 2001, Key West, Florida, USA, January 4-7, 2001. Society for Artificial Intelligence and Statistics 2001 [contents] - 2000
- [j4]Thomas S. Richardson:
Guest editorial. Stat. Comput. 10(1): 3-4 (2000)
1990 – 1999
- 1999
- [j3]Greg Ridgeway, Thomas Richardson, David Madigan:
Discussion on the paper by Friedman and Fisher. Stat. Comput. 9(2): 150-152 (1999) - [c10]Thomas Richardson, Heiko Bailer, Moulinath Banarjees:
Tractable structure search in the presence of latent variables. AISTATS 1999 - [c9]Greg Ridgeway, David Madigan, Thomas Richardson:
Boosting methodology for regression problems. AISTATS 1999 - 1998
- [c8]Greg Ridgeway, David Madigan, Thomas Richardson, John O'Kane:
Interpretable Boosted Naïve Bayes Classification. KDD 1998: 101-104 - [p1]Thomas S. Richardson:
Chain Graphs and Symmetric Associations. Learning in Graphical Models 1998: 231-259 - 1997
- [j2]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:
An evaluation of machine-learning methods for predicting pneumonia mortality. Artif. Intell. Medicine 9(2): 107-138 (1997) - [j1]Thomas Richardson:
A characterization of Markov equivalence for directed cyclic graphs. Int. J. Approx. Reason. 17(2-3): 107-162 (1997) - [c7]Thomas S. Richardson:
Extensions of Undirected and Acyclic, Directed Graphical Models. AISTATS 1997: 407-420 - [c6]Thomas S. Richardson, Peter Spirtes, Clark Glymour:
A Note on Cyclic Graphs and Dynamical Feedback Systems. AISTATS 1997: 421-428 - [c5]Peter Spirtes, Thomas S. Richardson, Christopher Meek:
Heuristic Greedy Search Algorithms for Latent Variable Models. AISTATS 1997: 481-488 - [c4]Peter Spirtes, Thomas S. Richardson:
A Polynomial Time Algorithm for Determining DAG Equivalence in the Presence of Latent Variables and Selection Bias. AISTATS 1997: 489-500 - 1996
- [c3]Thomas Richardson:
A Discovery Algorithm for Directed Cyclic Graphs. UAI 1996: 454-461 - [c2]Thomas Richardson:
A Polynomial-Time Algorithm for Deciding Equivalence of Directed Cyclic Graphical Models. UAI 1996: 462-469 - 1995
- [c1]Peter Spirtes, Christopher Meek, Thomas S. Richardson:
Causal Inference in the Presence of Latent Variables and Selection Bias. UAI 1995: 499-506
Coauthor Index
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