HyperSpace: Distributed Bayesian Hyperparameter Optimization. - M. Todd Young; Jacob D. Hinkle; Arvind Ramanathan; Ramakrishnan Kannan (SBAC-PAD, 2018)

Information Extraction from Cancer Pathology Reports with Graph Convolution Networks for Natural Language Texts. - Hong-Jun Yoon; John Gounley; M. Todd Young; Georgia D. Tourassi (IEEE BigData, 2019)

Exascale Deep Learning for Scientific Inverse Problems. - Nouamane Laanait; Joshua Romero; Junqi Yin; M. Todd Young; Sean Treichler; Vitalii Starchenko; Albina Y. Borisevich; Alex Sergeev; Michael A. Matheson (CoRR, 2019)

Challenges in Bayesian inference via Markov chain Monte Carlo for neural networks. - Theodore Papamarkou; Jacob D. Hinkle; M. Todd Young; David E. Womble (CoRR, 2019)

Towards the Development of Entropy-Based Anomaly Detection in an Astrophysics Simulation. - Drew Schmidt; Bronson Messer; M. Todd Young; Michael A. Matheson (CoRR, 2020)

Distributed Bayesian optimization of deep reinforcement learning algorithms. - M. Todd Young; Jacob D. Hinkle; Ramakrishnan Kannan; Arvind Ramanathan (J. Parallel Distributed Comput., 2020)

How Distinct Structural Flexibility within SARS-CoV-2 Spike Protein Reveals Potential Therapeutic Targets. - Serena H. Chen; M. Todd Young; John Gounley; Christopher B. Stanley; Debsindhu Bhowmik (IEEE BigData, 2021)

Limitations of Transformers on Clinical Text Classification. - Shang Gao 008; Mohammed M. Alawad; M. Todd Young; John Gounley; Noah Schaefferkoetter; Hong-Jun Yoon; Xiao-Cheng Wu; Eric B. Durbin; Jennifer A. Doherty; Antoinette Stroup; Linda Coyle; Georgia D. Tourassi (IEEE J. Biomed. Health Informatics, 2021)

Accelerating Collective Communication in Data Parallel Training across Deep Learning Frameworks. - Joshua Romero; Junqi Yin; Nouamane Laanait; Bing Xie; M. Todd Young; Sean Treichler; Vitalii Starchenko; Albina Y. Borisevich; Alex Sergeev; Michael A. Matheson (NSDI, 2022)