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ORCIDTyler H. McCormick
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2020 – today
- 2024
[i17]Kentaro Hoffman, Stephen Salerno, Awan Afiaz, Jeffrey T. Leek, Tyler H. McCormick:
Do We Really Even Need Data? CoRR abs/2401.08702 (2024)- [i16]Arun G. Chandrasekhar, Paul Goldsmith-Pinkham, Tyler H. McCormick, Samuel Thau, Jerry Wei:
Non-robustness of diffusion estimates on networks with measurement error. CoRR abs/2403.05704 (2024) - [i15]Aparajithan Venkateswaran, Anirudh Sankar, Arun G. Chandrasekhar, Tyler H. McCormick:
Robustly estimating heterogeneity in factorial data using Rashomon Partitions. CoRR abs/2404.02141 (2024) - [i14]Shuxian Fan, Adam Visokay
, Kentaro Hoffman, Stephen Salerno, Li Liu, Jeffrey T. Leek, Tyler H. McCormick:
From Narratives to Numbers: Valid Inference Using Language Model Predictions from Verbal Autopsy Narratives. CoRR abs/2404.02438 (2024) - [i13]Steven Wilkins-Reeves, Shane Lubold, Arun G. Chandrasekhar, Tyler H. McCormick:
Model-Based Inference and Experimental Design for Interference Using Partial Network Data. CoRR abs/2406.11940 (2024) - 2023
- [j6]Kathryn Turnbull, Christopher Nemeth, Matthew A. Nunes, Tyler H. McCormick:
Sequential estimation of temporally evolving latent space network models. Comput. Stat. Data Anal. 179: 107627 (2023) - [j5]Zehang Richard Li, Jason Thomas, Eungang Choi, Tyler H. McCormick, Samuel J. Clark:
The openVA Toolkit for Verbal Autopsies. R J. 14(4): 316-334 (2023) - [c6]Toshiya Yoshida, Trinity Shuxian Fan, Tyler H. McCormick, Zhenke Wu, Zehang Richard Li:
Bayesian Active Questionnaire Design for Cause-of-Death Assignment Using Verbal Autopsies. CHIL 2023: 37-49 - 2022
- [j4]Chunxiao Li, Cynthia Rudin, Tyler H. McCormick:
Rethinking Nonlinear Instrumental Variable Models through Prediction Validity. J. Mach. Learn. Res. 23: 96:1-96:55 (2022) - [j3]Wesley Lee, Tyler H. McCormick, Joshua Neil, Cole Sodja, Yanran Cui:
Anomaly Detection in Large-Scale Networks With Latent Space Models. Technometrics 64(2): 241-252 (2022) - [i12]Bolun Liu, Shane Lubold, Adrian E. Raftery, Tyler H. McCormick:
Bayesian Hyperbolic Multidimensional Scaling. CoRR abs/2210.15081 (2022) - [i11]Steven Wilkins-Reeves, Tyler H. McCormick:
Asymptotically Normal Estimation of Local Latent Network Curvature. CoRR abs/2211.11673 (2022) - 2021
- [c5]Mengjie Pan, Tyler H. McCormick, Bailey K. Fosdick:
Inference for Network Regression Models with Community Structure. ICML 2021: 8349-8358 - [i10]Tyler H. McCormick:
The "given data" paradigm undermines both cultures. CoRR abs/2105.12478 (2021) - [i9]Mengjie Pan, Tyler H. McCormick, Bailey K. Fosdick:
Inference for Network Regression Models with Community Structure. CoRR abs/2106.04271 (2021) - [i8]Shane Lubold, Bolun Liu, Tyler H. McCormick:
Spectral goodness-of-fit tests for complete and partial network data. CoRR abs/2106.09702 (2021) - 2020
- [i7]Shane Lubold, Arun G. Chandrasekhar, Tyler H. McCormick:
Identifying the latent space geometry of network models through analysis of curvature. CoRR abs/2012.10559 (2020)
2010 – 2019
- 2019
- [c4]Zehang Richard Li, Tyler H. McCormick, Samuel J. Clark:
Bayesian Joint Spike-and-Slab Graphical Lasso. ICML 2019: 3877-3885 - [i6]Emily Breza, Arun G. Chandrasekhar, Tyler H. McCormick, Mengjie Pan:
Consistently estimating graph statistics using Aggregated Relational Data. CoRR abs/1908.09881 (2019) - [i5]Wesley Lee, Tyler H. McCormick, Joshua Neil, Cole Sodja:
Anomaly Detection in Large Scale Networks with Latent Space Models. CoRR abs/1911.05522 (2019) - 2018
- [i4]Zehang Richard Li, Tyler H. McCormick, Samuel J. Clark:
Bayesian Joint Spike-and-Slab Graphical Lasso. CoRR abs/1805.07051 (2018) - 2017
- [i3]Tyler H. McCormick, Bailey K. Fosdick, Frank W. Marrs:
Standard errors for regression on relational data with exchangeable errors. CoRR abs/1701.05530 (2017) - [i2]Nina L. Cesare, Hedwig Lee, Tyler H. McCormick, Emma S. Spiro:
Redrawing the 'Color Line': Examining Racial Segregation in Associative Networks on Twitter. CoRR abs/1705.04401 (2017) - 2016
- [c3]Nina L. Cesare, Emma S. Spiro, Hedwig Lee, Tyler H. McCormick:
Examining Community Policing on Twitter: Precinct Use and Community Response. SocInfo (1) 2016: 155-167 - 2015
- [i1]Benjamin Letham, Cynthia Rudin, Tyler H. McCormick, David Madigan:
Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model. CoRR abs/1511.01644 (2015) - 2014
- [j2]Cynthia Rudin, Seyda Ertekin, Rebecca J. Passonneau, Axinia Radeva, Ashish Tomar, Boyi Xie, Stanley Lewis, Mark Riddle, Debbie Pangsrivinij, Tyler H. McCormick:
Analytics for Power Grid Distribution Reliability in New York City. Interfaces 44(4): 364-383 (2014) - [j1]Tyler H. McCormick, Rebecca Ferrell, Alan F. Karr, Patrick B. Ryan:
Big data, big results: Knowledge discovery in output from large-scale analytics. Stat. Anal. Data Min. 7(5): 404-412 (2014) - 2013
- [c2]Seyda Ertekin, Cynthia Rudin, Tyler H. McCormick:
Predicting Power Failures with Reactive Point Processes. AAAI (Late-Breaking Developments) 2013 - [c1]Benjamin Letham, Cynthia Rudin, Tyler H. McCormick, David Madigan:
An Interpretable Stroke Prediction Model using Rules and Bayesian Analysis. AAAI (Late-Breaking Developments) 2013
Coauthor Index
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