Learned Uncertainty-Aware (LUNA) Bases for Bayesian Regression using Multi-Headed Auxiliary Networks. - Sujay Thakur; Cooper Lorsung; Yaniv Yacoby; Finale Doshi-Velez; Weiwei Pan (CoRR, 2020)

Understanding Uncertainty in Bayesian Deep Learning. - Cooper Lorsung (CoRR, 2021)

AugLiChem: Data Augmentation Library ofChemical Structures for Machine Learning. - Rishikesh Magar; Yuyang Wang 005; Cooper Lorsung; Chen Liang; Hariharan Ramasubramanian; Peiyuan Li; Amir Barati Farimani (CoRR, 2021)

MeshDQN: A Deep Reinforcement Learning Framework for Improving Meshes in Computational Fluid Dynamics. - Cooper Lorsung; Amir Barati Farimani (CoRR, 2022)

AugLiChem: data augmentation library of chemical structures for machine learning. - Rishikesh Magar; Yuyang Wang 005; Cooper Lorsung; Chen Liang; Hariharan Ramasubramanian; Peiyuan Li; Amir Barati Farimani (Mach. Learn. Sci. Technol., 2022)

Neural Network Predicts Ion Concentration Profiles under Nanoconfinement. - Zhonglin Cao; Yuyang Wang 005; Cooper Lorsung; Amir Barati Farimani (CoRR, 2023)

Physics Informed Token Transformer. - Cooper Lorsung; Zijie Li; Amir Barati Farimani (CoRR, 2023)

PICL: Physics Informed Contrastive Learning for Partial Differential Equations. - Cooper Lorsung; Amir Barati Farimani (CoRR, 2024)

Explain Like I'm Five: Using LLMs to Improve PDE Surrogate Models with Text. - Cooper Lorsung; Amir Barati Farimani (CoRR, 2024)

Strategies for Pretraining Neural Operators. - Anthony Y. Zhou; Cooper Lorsung; AmirPouya Hemmasian; Amir Barati Farimani (Trans. Mach. Learn. Res., 2024)

Physics informed token transformer for solving partial differential equations. - Cooper Lorsung; Zijie Li; Amir Barati Farimani (Mach. Learn. Sci. Technol., 2024)