Thomas F. Miller III

Orcid: 0000-0002-1882-5380

According to our database1, Thomas F. Miller III authored at least 15 papers between 2019 and 2024.

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Bibliography

2024
State-specific protein-ligand complex structure prediction with a multiscale deep generative model.
Nat. Mac. Intell., 2024

2023
NeuralPLexer evaluation datasets and predictions.
Dataset, December, 2023

#COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol.
Int. J. High Perform. Comput. Appl., 2023

2022
Dynamic-Backbone Protein-Ligand Structure Prediction with Multiscale Generative Diffusion Models.
CoRR, 2022

Molecular-orbital-based Machine Learning for Open-shell and Multi-reference Systems with Kernel Addition Gaussian Process Regression.
CoRR, 2022

Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-orbital-based Machine Learning.
CoRR, 2022

Accurate Molecular-Orbital-Based Machine Learning Energies via Unsupervised Clustering of Chemical Space.
CoRR, 2022

2021
Molecular Energy Learning Using Alternative Blackbox Matrix-Matrix Multiplication Algorithm for Exact Gaussian Process.
CoRR, 2021

UNiTE: Unitary N-body Tensor Equivariant Network with Applications to Quantum Chemistry.
CoRR, 2021

2020
Multi-task learning for electronic structure to predict and explore molecular potential energy surfaces.
CoRR, 2020

A generalized class of strongly stable and dimension-free T-RPMD integrators.
CoRR, 2020

OrbNet: Deep Learning for Quantum Chemistry Using Symmetry-Adapted Atomic-Orbital Features.
CoRR, 2020

2019
Dimension-free path-integral molecular dynamics without preconditioning.
CoRR, 2019

Regression-clustering for Improved Accuracy and Training Cost with Molecular-Orbital-Based Machine Learning.
CoRR, 2019

A Universal Density Matrix Functional from Molecular Orbital-Based Machine Learning: Transferability across Organic Molecules.
CoRR, 2019


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