Web-based design and evaluation of T-cell vaccine candidates. - James Thurmond; Hyejin Yoon; Carla Kuiken; Karina Yusim; Simon Perkins; James Theiler; Tanmoy Bhattacharya 001; Bette T. Korber; Will Fischer 001 (Bioinform., 2008)

Estimating time since infection in early homogeneous HIV-1 samples using a poisson model. - Elena E. Giorgi; Bob Funkhouser; Gayathri Athreya; Alan S. Perelson; Bette T. Korber; Tanmoy Bhattacharya 001 (BMC Bioinform., 2010)

Genetic Signatures in the Envelope Glycoproteins of HIV-1 that Associate with Broadly Neutralizing Antibodies. - S. Gnanakaran; Marcus G. Daniels; Tanmoy Bhattacharya 001; Alan S. Lapedes; Anurag Sethi; Ming Li; Haili Tang; Kelli Greene; Hongmei Gao; Barton F. Haynes; Myron S. Cohen; George M. Shaw; et al. (PLoS Comput. Biol., 2010)

On the universal structure of human lexical semantics. - Hyejin Youn; Logan Sutton; Eric Smith; Cristopher Moore; Jon F. Wilkins; Ian Maddieson; William Croft 001; Tanmoy Bhattacharya 001 (CoRR, 2015)

A Likelihood Ratio Detector for Identifying Within-Perimeter Computer Network Attacks. - Justin Grana; David H. Wolpert; Joshua Neil; Dongping Xie; Tanmoy Bhattacharya 001; Russell Bent (CoRR, 2016)

A likelihood ratio anomaly detector for identifying within-perimeter computer network attacks. - Justin Grana; David H. Wolpert; Joshua Neil; Dongping Xie; Tanmoy Bhattacharya 001; Russell Bent (J. Netw. Comput. Appl., 2016)

Leveraging Large-Scale Computing for Population Information Integration, Analysis, and Modeling. - Jessica A. Boten; Donna R. Rivera; Madhumita Myneni; Georgia D. Tourassi; Tanmoy Bhattacharya 001; Ana Paula de Oliveira Sales; Thomas S. Brettin; Paul A. Fearn; Lynne Penberthy (AMIA, 2017)

CAT: computer aided triage improving upon the Bayes risk through ε-refusal triage rules. - Nicolas W. Hengartner; Leticia Cuellar; Xiao-Cheng Wu; Georgia D. Tourassi; John X. Qiu; James Blair Christian; Tanmoy Bhattacharya 001 (BMC Bioinform., 2018)

Combating Label Noise in Deep Learning using Abstention. - Sunil Thulasidasan; Tanmoy Bhattacharya 001; Jeff A. Bilmes; Gopinath Chennupati; Jamal Mohd-Yusof (ICML, 2019)

On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks. - Sunil Thulasidasan; Gopinath Chennupati; Jeff A. Bilmes; Tanmoy Bhattacharya 001; Sarah Michalak (NeurIPS, 2019)

The need for uncertainty quantification in machine-assisted medical decision making. - Edmon Begoli; Tanmoy Bhattacharya 001; Dimitri Kusnezov (Nat. Mach. Intell., 2019)

Why I'm not Answering: Understanding Determinants of Classification of an Abstaining Classifier for Cancer Pathology Reports. - Sayera Dhaubhadel; Jamaludin Mohd-Yusof; Kumkum Ganguly; Gopinath Chennupati; Sunil Thulasidasan; Nicolas W. Hengartner; Brent J. Mumphrey; Eric B. Durbin; Jennifer A. Doherty; Mireille Lemieux; Noah Schaefferkoetter; Georgia D. Tourassi; et al. (CoRR, 2020)

Uncertainty Bounds for Multivariate Machine Learning Predictions on High-Strain Brittle Fracture. - Cristina Garcia-Cardona; M. Giselle Fernández-Godino; Daniel O'Malley; Tanmoy Bhattacharya 001 (CoRR, 2020)

An Effective Baseline for Robustness to Distributional Shift. - Sunil Thulasidasan; Sushil Thapa; Sayera Dhaubhadel; Gopinath Chennupati; Tanmoy Bhattacharya 001; Jeff A. Bilmes (ICMLA, 2021)

Deep learning uncertainty quantification for clinical text classification. - Alina Peluso; Ioana Danciu; Hong-Jun Yoon; Jamaludin Mohd-Yusof; Tanmoy Bhattacharya 001; Adam Spannaus; Noah Schaefferkoetter; Eric B. Durbin; Xiao-Cheng Wu; Antoinette Stroup; Jennifer A. Doherty; Stephen M. Schwartz; et al. (J. Biomed. Informatics, 2024)

Global explainability of a deep abstaining classifier. - Sayera Dhaubhadel; Jamaludin Mohd-Yusof; Benjamin H. McMahon; Trilce Estrada; Kumkum Ganguly; Adam Spannaus; John P. Gounley; Xiao-Cheng Wu; Eric B. Durbin; Heidi A. Hanson; Tanmoy Bhattacharya 001 (CoRR, 2025)