Efficient automated marshaling of C++ data structures for MPI applications. - Wesley Tansey; Eli Tilevich (IPDPS, 2008)

DeXteR- An Extensible Framework for Declarative Parameter Passing in Distributed Object Systems. - Sriram Gopal; Wesley Tansey; Gokulnath C. Kannan; Eli Tilevich (Middleware, 2008)

Annotation refactoring: inferring upgrade transformations for legacy applications. - Wesley Tansey; Eli Tilevich (OOPSLA, 2008)

Trailblazer: a tool for automated annotation refactoring. - Myoungkyu Song; Eli Tilevich; Wesley Tansey (OOPSLA Companion, 2009)

Accelerating evolution via egalitarian social learning. - Wesley Tansey; Eliana Feasley; Risto Miikkulainen (GECCO, 2012)

Multiagent Learning through Neuroevolution. - Risto Miikkulainen; Eliana Feasley; Leif M. Johnson; Igor Karpov; Padmini Rajagopalan; Aditya Rawal; Wesley Tansey (WCCI, 2012)

Vector-Space Markov Random Fields via Exponential Families. - Wesley Tansey; Oscar Hernan Madrid Padilla; Arun Sai Suggala; Pradeep Ravikumar (ICML, 2015)

Diet2Vec: Multi-scale analysis of massive dietary data. - Wesley Tansey; Edward W. Lowe Jr.; James G. Scott (CoRR, 2016)

Leaf-Smoothed Hierarchical Softmax for Ordinal Prediction. - Wesley Tansey; Karl Pichotta; James G. Scott (AAAI, 2018)

Maximum-Variance Total Variation Denoising for Interpretable Spatial Smoothing. - Wesley Tansey; Jesse Thomason; James G. Scott (AAAI, 2018)

Black Box FDR. - Wesley Tansey; Yixin Wang 002; David M. Blei; Raul Rabadan (ICML, 2018)

Interpreting Black Box Models with Statistical Guarantees. - Collin Burns; Jesse Thomason; Wesley Tansey (CoRR, 2019)

Bayesian Tensor Filtering: Smooth, Locally-Adaptive Factorization of Functional Matrices. - Wesley Tansey; Christopher Tosh; David M. Blei (CoRR, 2019)

Selected Papers from the Workshop on Computational Biology: Joint with the International Joint Conference on Artificial Intelligence and the International Conference on Machine Learning, 2018. - Abdoulaye Baniré Diallo; Engelbert Mephu Nguifo; Wajdi Dhifli; Elham Azizi; Sandhya Prabhakaran; Wesley Tansey (J. Comput. Biol., 2019)

Interpreting Black Box Models via Hypothesis Testing. - Collin Burns; Jesse Thomason; Wesley Tansey (FODS, 2020)

Deep Direct Likelihood Knockoffs. - Mukund Sudarshan; Wesley Tansey; Rajesh Ranganath (NeurIPS, 2020)

Targeted active learning for probabilistic models. - Christopher Tosh; Mauricio Tec; Wesley Tansey (CoRR, 2022)

The Holdout Randomization Test for Feature Selection in Black Box Models. - Wesley Tansey; Victor Veitch; Haoran Zhang; Raul Rabadan; David M. Blei (J. Comput. Graph. Stat., 2022)

Quantile regression with ReLU Networks: Estimators and minimax rates. - Oscar Hernan Madrid Padilla; Wesley Tansey; Yanzhen Chen (J. Mach. Learn. Res., 2022)

DIET: Conditional independence testing with marginal dependence measures of residual information. - Mukund Sudarshan; Aahlad Manas Puli; Wesley Tansey; Rajesh Ranganath (AISTATS, 2023)

Scalable Causal Structure Learning via Amortized Conditional Independence Testing. - James Leiner; Brian Manzo; Aaditya Ramdas; Wesley Tansey (CLeaR, 2025)

Treatment response as a latent variable. - Christopher Tosh; Boyuan Zhang; Wesley Tansey (CoRR, 2025)

Controllable diffusion-based generation for multi-channel biological data. - Haoran Zhang; Mingyuan Zhou; Wesley Tansey (CoRR, 2025)