Andrew J. Medford

According to our database, Andrew J. Medford authored at least 13 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Maximum-likelihood estimators in physics-informed neural networks for high-dimensional inverse problems.

Gabriel S. Gusmão, Andrew J. Medford

Comput. Chem. Eng., February, 2024

2023

AmpTorch: A Python package for scalable fingerprint-based neural network training on multi-element systems with integrated uncertainty quantification.

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

J. Open Source Softw., 2023

Soft and transferable pseudopotentials from multi-objective optimization.

Mostafa Faghih Shojaei, John E. Pask, Andrew J. Medford, Phanish Suryanarayana

Comput. Phys. Commun., 2023

The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture.

Anuroop Sriram, Sihoon Choi, Xiaohan Yu, Logan M. Brabson, Abhishek Das, Zachary W. Ulissi, Matt Uyttendaele, Andrew J. Medford, David S. Sholl

CoRR, 2023

Model-based design of temporal analysis of products (TAP) reactors: A simulated case study in oxidative propane dehydrogenation.

Adam C. Yonge, Gabriel S. Gusmão, Rebecca Fushimi, Andrew J. Medford

CoRR, 2023

2022

Robust and scalable uncertainty estimation with conformal prediction for machine-learned interatomic potentials.

Yuge Hu, Joseph Musielewicz, Zachary W. Ulissi, Andrew J. Medford

Mach. Learn. Sci. Technol., December, 2022

2021

SPARC: Simulation Package for Ab-initio Real-space Calculations.

Qimen Xu, Abhiraj Sharma, Benjamin M. Comer, Hua Huang, Edmond Chow, Andrew J. Medford, John E. Pask, Phanish Suryanarayana

SoftwareX, 2021

A Priori Calibration of Transient Kinetics Data via Machine Learning.

M. Ross Kunz, Adam Yonge, Rakesh Batchu, Zongtang Fang, Yixiao Wang, Gregory Yablonsky, Andrew J. Medford, Rebecca Fushimi

CoRR, 2021

A Universal Framework for Featurization of Atomistic Systems.

Xiangyun Lei, Andrew J. Medford

CoRR, 2021

2020

Kinetics-Informed Neural Networks.

Gabriel S. Gusmão, Adhika P. Retnanto, Shashwati C. da Cunha, Andrew J. Medford

CoRR, 2020

Population Susceptibility Variation and Its Effect on Contagion Dynamics.

Christopher Rose, Andrew J. Medford, C. Franklin Goldsmith, Tejs Vegge, Joshua Weitz, Andrew A. Peterson

CoRR, 2020

TAPsolver: A Python package for the simulation and analysis of TAP reactor experiments.

Adam Yonge, M. Ross Kunz, Rakesh Batchu, Zongtang Fang, Tobin Issac, Rebecca Fushimi, Andrew J. Medford

CoRR, 2020

2019

ElectroLens: Understanding Atomistic Simulations through Spatially-Resolved Visualization of High-Dimensional Features.

Xiangyun Lei, Fred Hohman, Duen Horng (Polo) Chau, Andrew J. Medford

Proceedings of the 30th IEEE Visualization Conference, 2019