Andrew J. Medford

22 papers Journal 21Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Modeling Batch Crystallization under Uncertainty Using Physics-informed Machine Learning. CoRR Dingqi Nai, Huayu Li, Martha Grover, Andrew J. Medford
2025	J	`jnl`	D-MOPH-25: diverse MOF-molecule pairs for Henry's constants prediction Mach. Learn. Sci. Technol. Sihoon Choi, David S. Sholl, Andrew J. Medford
2025	J	`jnl`	Prospects for Using Artificial Intelligence to Understand Intrinsic Kinetics of Heterogeneous Catalytic Reactions. CoRR Andrew J. Medford, Todd N. Whittaker, Bjarne Kreitz, David W. Flaherty, John R. Kitchin
2025	J	`jnl`	SPARC-X-API: Versatile Python Interface for Real-space Density Functional Theory Calculations. J. Open Source Softw. Tian Tian, Lucas R. Timmerman, Shashikant Kumar, Benjamin M. Comer, Andrew J. Medford, Phanish Suryanarayana
2025	J	`jnl`	Spectral scheme for atomic structure calculations in density functional theory. Comput. Phys. Commun. Sayan Bhowmik, John E. Pask, Andrew J. Medford, Phanish Suryanarayana
2024	J	`jnl`	Fitting micro-kinetic models to transient kinetics of temporal analysis of product reactors using kinetics-informed neural networks. CoRR Dingqi Nai, Gabriel S. Gusmão, Zachary A. Kilwein, Fani Boukouvala, Andrew J. Medford
2024	J	`jnl`	Maximum-likelihood estimators in physics-informed neural networks for high-dimensional inverse problems. Comput. Chem. Eng. Gabriel S. Gusmão, Andrew J. Medford
2024	J	`jnl`	SPARC v2.0.0: Spin-orbit coupling, dispersion interactions, and advanced exchange-correlation functionals. Softw. Impacts Boqin Zhang, Xin Jing, Qimen Xu, Shashikant Kumar, Abhiraj Sharma, Lucas Erlandson, Sushree Jagriti Sahoo, Edmond Chow, Andrew J. Medford, John E. Pask, Phanish Suryanarayana
2023	J	`jnl`	AmpTorch: A Python package for scalable fingerprint-based neural network training on multi-element systems with integrated uncertainty quantification. J. Open Source Softw. Muhammed Shuaibi, Yuge Hu, Xiangyun Lei, Benjamin M. Comer, Matt Adams, Jacob Paras, Rui Qi Chen, Eric Musa, Joseph Musielewicz, Andrew A. Peterson, Andrew J. Medford, Zachary W. Ulissi
2023	J	`jnl`	Maximum-likelihood Estimators in Physics-Informed Neural Networks for High-dimensional Inverse Problems. CoRR Gabriel S. Gusmão, Andrew J. Medford
2023	J	`jnl`	Model-based design of temporal analysis of products (TAP) reactors: A simulated case study in oxidative propane dehydrogenation. CoRR Adam C. Yonge, Gabriel S. Gusmão, Rebecca Fushimi, Andrew J. Medford
2023	J	`jnl`	Soft and transferable pseudopotentials from multi-objective optimization. Comput. Phys. Commun. Mostafa Faghih Shojaei, John E. Pask, Andrew J. Medford, Phanish Suryanarayana
2023	J	`jnl`	The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture. CoRR Anuroop Sriram, Sihoon Choi, Xiaohan Yu, Logan M. Brabson, Abhishek Das, Zachary W. Ulissi, Matt Uyttendaele, Andrew J. Medford, David S. Sholl
2022	J	`jnl`	Robust and scalable uncertainty estimation with conformal prediction for machine-learned interatomic potentials. Mach. Learn. Sci. Technol. Yuge Hu, Joseph Musielewicz, Zachary W. Ulissi, Andrew J. Medford
2021	J	`jnl`	A Priori Calibration of Transient Kinetics Data via Machine Learning. CoRR M. Ross Kunz, Adam Yonge, Rakesh Batchu, Zongtang Fang, Yixiao Wang, Gregory S. Yablonsky, Andrew J. Medford, Rebecca Fushimi
2021	J	`jnl`	A Universal Framework for Featurization of Atomistic Systems. CoRR Xiangyun Lei, Andrew J. Medford
2021	J	`jnl`	SPARC: Simulation Package for Ab-initio Real-space Calculations. SoftwareX Qimen Xu, Abhiraj Sharma, Benjamin M. Comer, Hua Huang, Edmond Chow, Andrew J. Medford, John E. Pask, Phanish Suryanarayana
2020	J	`jnl`	Kinetics-Informed Neural Networks. CoRR Gabriel S. Gusmão, Adhika P. Retnanto, Shashwati C. da Cunha, Andrew J. Medford
2020	J	`jnl`	Population Susceptibility Variation and Its Effect on Contagion Dynamics. CoRR Christopher Rose, Andrew J. Medford, C. Franklin Goldsmith, Tejs Vegge, Joshua Weitz, Andrew A. Peterson
2020	J	`jnl`	TAPsolver: A Python package for the simulation and analysis of TAP reactor experiments. CoRR Adam Yonge, M. Ross Kunz, Rakesh Batchu, Zongtang Fang, Tobin Issac, Rebecca Fushimi, Andrew J. Medford
2019	J	`jnl`	ElectroLens: Understanding Atomistic Simulations Through Spatially-resolved Visualization of High-dimensional Features. CoRR Xiangyun Lei, Fred Hohman, Duen Horng Chau, Andrew J. Medford
2019	—	`conf`	ElectroLens: Understanding Atomistic Simulations through Spatially-Resolved Visualization of High-Dimensional Features. IEEE VIS (Short Papers) Xiangyun Lei, Fred Hohman, Duen Horng (Polo) Chau, Andrew J. Medford