John S. Schreck

14 papers Journal 14

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Bayesian Deep Learning for Convective Initiation Nowcasting Uncertainty Estimation. CoRR Da Fan, David John Gagne II, Steven J. Greybush, Eugene E. Clothiaux, John S. Schreck, Chaopeng Shen
2025	J	`jnl`	Controllable Probabilistic Forecasting with Stochastic Decomposition Layers. CoRR John S. Schreck, William E. Chapman, Charlie Becker, David John Gagne II, Dhamma Kimpara, Nihanth Cherukuru, Judith Berner, Kirsten J. Mayer, Negin Sobhani
2025	J	`jnl`	Investigating the contribution of terrain-following coordinates and conservation schemes in AI-driven precipitation forecasts. CoRR Yingkai Sha, John S. Schreck, William E. Chapman, David John Gagne II
2025	J	`jnl`	Reinforcement Learning (RL) Meets Urban Climate Modeling: Investigating the Efficacy and Impacts of RL-Based HVAC Control. CoRR Junjie Yu, John S. Schreck, David John Gagne, Keith W. Oleson, Jie Li, Yongtu Liang, Qi Liao, Mingfei Sun, David O. Topping, Zhonghua Zheng
2025	J	`jnl`	Uncertainty Quantification of Wind Gust Predictions in the Northeast US: An Evidential Neural Network and Explainable Artificial Intelligence Approach. CoRR Israt Jahan, John S. Schreck, David John Gagne, Charlie Becker, Marina Astitha
2025	J	`jnl`	Uncertainty quantification of wind gust predictions in the northeast United States: An evidential neural network and explainable artificial intelligence approach. Environ. Model. Softw. Israt Jahan, John S. Schreck, David John Gagne, Charlie Becker, Marina Astitha
2024	J	`jnl`	Community Research Earth Digital Intelligence Twin (CREDIT). CoRR John S. Schreck, Yingkai Sha, William E. Chapman, Dhamma Kimpara, Judith Berner, Seth McGinnis, Arnold Kazadi, Negin Sobhani, Ben Kirk, David John Gagne II
2023	J	`jnl`	Evidential Deep Learning: Enhancing Predictive Uncertainty Estimation for Earth System Science Applications. CoRR 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, Belen Saavedra, Justin Willson, Christopher D. Wirz
2023	J	`jnl`	Machine Learning and VIIRS Satellite Retrievals for Skillful Fuel Moisture Content Monitoring in Wildfire Management. CoRR John S. Schreck, William Petzke, Pedro A. Jimenez, Thomas Brummet, Jason C. Knievel, Eric James, Branko Kosovic, David John Gagne
2023	J	`jnl`	Machine Learning and VIIRS Satellite Retrievals for Skillful Fuel Moisture Content Monitoring in Wildfire Management. Remote. Sens. John S. Schreck, William Petzke, Pedro A. Jimenez, Thomas Brummet, Jason C. Knievel, Eric James, Branko Kosovic, David John Gagne
2023	J	`jnl`	Mimicking non-ideal instrument behavior for hologram processing using neural style translation. CoRR John S. Schreck, Matthew Hayman, Gabrielle Gantos, Aaron Bansemer, David John Gagne
2022	J	`jnl`	Generative and interpretable machine learning for aptamer design and analysis of in vitro sequence selection. PLoS Comput. Biol. Andrea Di Gioacchino, Jonah Procyk, Marco Molari, John S. Schreck, Yu Zhou, Yan Liu, Rémi Monasson, Simona Cocco, Petr Sulc
2022	J	`jnl`	Neural network processing of holographic images. CoRR John S. Schreck, Gabrielle Gantos, Matthew Hayman, Aaron Bansemer, David John Gagne
2019	J	`jnl`	Learning retrosynthetic planning through self-play. CoRR John S. Schreck, Connor W. Coley, Kyle J. M. Bishop