Learning retrosynthetic planning through self-play. - John S. Schreck; Connor W. Coley; Kyle J. M. Bishop (CoRR, 2019)

Neural network processing of holographic images. - John S. Schreck; Gabrielle Gantos; Matthew Hayman; Aaron Bansemer; David John Gagne (CoRR, 2022)

Generative and interpretable machine learning for aptamer design and analysis of in vitro sequence selection. - Andrea Di Gioacchino; Jonah Procyk; Marco Molari; John S. Schreck; Yu Zhou; Yan Liu; Rémi Monasson; Simona Cocco; Petr Sulc (PLoS Comput. Biol., 2022)

Mimicking non-ideal instrument behavior for hologram processing using neural style translation. - John S. Schreck; Matthew Hayman; Gabrielle Gantos; Aaron Bansemer; David John Gagne (CoRR, 2023)

Evidential Deep Learning: Enhancing Predictive Uncertainty Estimation for Earth System Science Applications. - John S. Schreck; David John Gagne II; Charlie Becker; William E. Chapman; Kim Elmore; Gabrielle Gantos; Eliot Kim; Dhamma Kimpara; Thomas Martin; Maria J. Molina; Vanessa M. Pryzbylo; Jacob Radford; et al. (CoRR, 2023)

Machine Learning and VIIRS Satellite Retrievals for Skillful Fuel Moisture Content Monitoring in Wildfire Management. - John S. Schreck; William Petzke; Pedro A. Jimenez; Thomas Brummet; Jason C. Knievel; Eric James; Branko Kosovic; David John Gagne (Remote. Sens., 2023)

Community Research Earth Digital Intelligence Twin (CREDIT). - John S. Schreck; Yingkai Sha; William E. Chapman; Dhamma Kimpara; Judith Berner; Seth McGinnis; Arnold Kazadi; Negin Sobhani; Ben Kirk; David John Gagne II (CoRR, 2024)

Uncertainty quantification of wind gust predictions in the northeast United States: An evidential neural network and explainable artificial intelligence approach. - Israt Jahan; John S. Schreck; David John Gagne; Charlie Becker; Marina Astitha (Environ. Model. Softw., 2025)

Uncertainty Quantification of Wind Gust Predictions in the Northeast US: An Evidential Neural Network and Explainable Artificial Intelligence Approach. - Israt Jahan; John S. Schreck; David John Gagne; Charlie Becker; Marina Astitha (CoRR, 2025)

Investigating the contribution of terrain-following coordinates and conservation schemes in AI-driven precipitation forecasts. - Yingkai Sha; John S. Schreck; William E. Chapman; David John Gagne II (CoRR, 2025)

Reinforcement Learning (RL) Meets Urban Climate Modeling: Investigating the Efficacy and Impacts of RL-Based HVAC Control. - Junjie Yu; John S. Schreck; David John Gagne; Keith W. Oleson; Jie Li; Yongtu Liang; Qi Liao 001; Mingfei Sun 001; David O. Topping; Zhonghua Zheng (CoRR, 2025)

Bayesian Deep Learning for Convective Initiation Nowcasting Uncertainty Estimation. - Da Fan; David John Gagne II; Steven J. Greybush; Eugene E. Clothiaux; John S. Schreck; Chaopeng Shen (CoRR, 2025)