Thomas F. Miller III

15 papers Journal 15

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	NeuralPLexer3: Accurate Biomolecular Complex Structure Prediction with Flow Models. CoRR Zhuoran Qiao, Feizhi Ding, Thomas Dresselhaus, Mia A. Rosenfeld, Xiaotian Han, Owen Howell, Aniketh Iyengar, Stephen Opalenski, Anders S. Christensen, Sai K. Sirumalla, Frederick R. Manby, Thomas F. Miller III, Matthew Welborn
2024	J	`jnl`	State-specific protein-ligand complex structure prediction with a multiscale deep generative model. Nat. Mac. Intell. Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller III, Animashree Anandkumar
2023	J	`jnl`	#COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol. Int. J. High Perform. Comput. Appl. Abigail C. Dommer, Lorenzo Casalino, Fiona L. Kearns, Mia A. Rosenfeld, Nicholas Wauer, Surl-Hee Ahn, John Russo, A. Sofia F. Oliveira, Clare Morris, Anthony T. Bogetti, Anda Trifan, Alexander Brace, Terra Sztain, Austin Clyde, Heng Ma, S. Chakra Chennubhotla, Hyungro Lee, Matteo Turilli, Syma Khalid, Teresa Tamayo-Mendoza, Matthew Welborn, Anders S. Christensen, Daniel G. A. Smith, Zhuoran Qiao, Sai K. Sirumalla, Michael O'Connor, Frederick R. Manby, Anima Anandkumar, David J. Hardy, James C. Phillips, Abraham C. Stern, Josh Romero, David Clark, Mitchell Dorrell, Tom Maiden, Lei Huang, John D. McCalpin, Christopher J. Woods, Alan Gray, Matt Williams, Bryan Barker, Harinda Rajapaksha, Richard Pitts, Tom Gibbs, John E. Stone, Daniel M. Zuckerman, Adrian J. Mulholland, Thomas F. Miller III, Shantenu Jha, Arvind Ramanathan, Lillian T. Chong, Rommie E. Amaro
2022	J	`jnl`	Accurate Molecular-Orbital-Based Machine Learning Energies via Unsupervised Clustering of Chemical Space. CoRR Lixue Cheng, Jiace Sun, Thomas F. Miller III
2022	J	`jnl`	Dynamic-Backbone Protein-Ligand Structure Prediction with Multiscale Generative Diffusion Models. CoRR Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller III, Anima Anandkumar
2022	J	`jnl`	Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-orbital-based Machine Learning. CoRR Jiace Sun, Lixue Cheng, Thomas F. Miller III
2022	J	`jnl`	Molecular-orbital-based Machine Learning for Open-shell and Multi-reference Systems with Kernel Addition Gaussian Process Regression. CoRR Lixue Cheng, Jiace Sun, J. Emiliano Deustua, Vignesh C. Bhethanabotla, Thomas F. Miller III
2021	J	`jnl`	Molecular Energy Learning Using Alternative Blackbox Matrix-Matrix Multiplication Algorithm for Exact Gaussian Process. CoRR Jiace Sun, Lixue Cheng, Thomas F. Miller III
2021	J	`jnl`	UNiTE: Unitary N-body Tensor Equivariant Network with Applications to Quantum Chemistry. CoRR Zhuoran Qiao, Anders S. Christensen, Frederick R. Manby, Matthew Welborn, Anima Anandkumar, Thomas F. Miller III
2020	J	`jnl`	A generalized class of strongly stable and dimension-free T-RPMD integrators. CoRR Jorge L. Rosa-Raíces, Jiace Sun, Nawaf Bou-Rabee, Thomas F. Miller III
2020	J	`jnl`	Multi-task learning for electronic structure to predict and explore molecular potential energy surfaces. CoRR Zhuoran Qiao, Feizhi Ding, Matthew Welborn, Peter J. Bygrave, Daniel G. A. Smith, Animashree Anandkumar, Frederick R. Manby, Thomas F. Miller III
2020	J	`jnl`	OrbNet: Deep Learning for Quantum Chemistry Using Symmetry-Adapted Atomic-Orbital Features. CoRR Zhuoran Qiao, Matthew Welborn, Animashree Anandkumar, Frederick R. Manby, Thomas F. Miller III
2019	J	`jnl`	A Universal Density Matrix Functional from Molecular Orbital-Based Machine Learning: Transferability across Organic Molecules. CoRR Lixue Cheng, Matthew Welborn, Thomas F. Miller III
2019	J	`jnl`	Dimension-free path-integral molecular dynamics without preconditioning. CoRR Roman Korol, Nawaf Bou-Rabee, Thomas F. Miller III
2019	J	`jnl`	Regression-clustering for Improved Accuracy and Training Cost with Molecular-Orbital-Based Machine Learning. CoRR Lixue Cheng, Nikola B. Kovachki, Matthew Welborn, Thomas F. Miller III