p7physics.chem-ph

physics.chem-ph

43 papers

Challenges in Large Scale Quantum Mechanical Calculations

Laura E. Ratcliff, Stephan Mohr, Georg Huhs, Thierry Deutsch, Michel Masella, Luigi Genovese

1609.00252

SchNet: A continuous-filter convolutional neural network for modeling quantum interactions

Kristof T. Schütt, Pieter-Jan Kindermans, Huziel E. Sauceda, Stefan Chmiela, Alexandre Tkatchenko, Klaus-Robert Müller

1706.08566

Robust and efficient configurational molecular sampling via Langevin Dynamics

Benedict Leimkuhler, Charles Matthews

1304.3269

Emergent autonomous scientific research capabilities of large language models

Daniil A. Boiko, Robert MacKnight, Gabe Gomes

2304.05332

Using nonequilibrium fluctuation theorems to understand and correct errors in equilibrium and nonequilibrium discrete Langevin dynamics simulations

David A. Sivak, John D. Chodera, Gavin E. Crooks

1107.2967

Rational Construction of Stochastic Numerical Methods for Molecular Sampling

Benedict Leimkuhler, Charles Matthews

1203.5428

Stochastic Normalizing Flows

Hao Wu, Jonas Köhler, Frank Noé

2002.06707

Machine Learning Force Fields

Oliver T. Unke, Stefan Chmiela, Huziel E. Sauceda, Michael Gastegger, Igor Poltavsky, Kristof T. Schütt, Alexandre Tkatchenko, Klaus-Robert Müller

2010.07067

Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems

John A. Keith, Valentin Vassilev-Galindo, Bingqing Cheng, Stefan Chmiela, Michael Gastegger, Klaus-Robert Müller, Alexandre Tkatchenko

2102.06321

Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics

Christoph Wehmeyer, Frank Noé

1710.11239

Quantum-Chemical Insights from Deep Tensor Neural Networks

Kristof T. Schütt, Farhad Arbabzadah, Stefan Chmiela, Klaus R. Müller, Alexandre Tkatchenko

1609.08259

Automatic chemical design using a data-driven continuous representation of molecules

Rafael Gómez-Bombarelli, Jennifer N. Wei, David Duvenaud, José Miguel Hernández-Lobato, Benjamín Sánchez-Lengeling, Dennis Sheberla, Jorge Aguilera-Iparraguirre, Timothy D. Hirzel, Ryan P. Adams, Alán Aspuru-Guzik

1610.02415

Targeted free energy estimation via learned mappings

Peter Wirnsberger, Andrew J. Ballard, George Papamakarios, Stuart Abercrombie, Sébastien Racanière, Alexander Pritzel, Danilo Jimenez Rezende, Charles Blundell

2002.04913

Adaptive Thermostats for Noisy Gradient Systems

Benedict Leimkuhler, Xiaocheng Shang

1505.06889

Machine learning of solvent effects on molecular spectra and reactions

Michael Gastegger, Kristof T. Schütt, Klaus-Robert Müller

2010.14942

A Fourth-Generation High-Dimensional Neural Network Potential with Accurate Electrostatics Including Non-local Charge Transfer

Tsz Wai Ko, Jonas A. Finkler, Stefan Goedecker, Jörg Behler

2009.06484

Equivariant Flows: sampling configurations for multi-body systems with symmetric energies

Jonas Köhler, Leon Klein, Frank Noé

1910.00753

Physics-inspired structural representations for molecules and materials

Felix Musil, Andrea Grisafi, Albert P. Bartók, Christoph Ortner, Gábor Csányi, Michele Ceriotti

2101.04673

Machine Learning in QM/MM Molecular Dynamics Simulations of Condensed-Phase Systems

Lennard Böselt, Moritz Thürlemann, Sereina Riniker

2010.11610

Learning Gradient Fields for Molecular Conformation Generation

Chence Shi, Shitong Luo, Minkai Xu, Jian Tang

2105.03902

Ab-Initio Solution of the Many-Electron Schrödinger Equation with Deep Neural Networks

David Pfau, James S. Spencer, Alexander G. de G. Matthews, W. M. C. Foulkes

1909.02487

Big Data meets Quantum Chemistry Approximations: The $Δ$-Machine Learning Approach

Raghunathan Ramakrishnan, Pavlo O. Dral, Matthias Rupp, O. Anatole von Lilienfeld

1503.04987

On the Completeness of Atomic Structure Representations

Sergey N. Pozdnyakov, Michael J. Willatt, Albert P. Bartók, Christoph Ortner, Gábor Csányi, Michele Ceriotti

2001.11696

Machine Learning of Accurate Energy-Conserving Molecular Force Fields

Stefan Chmiela, Alexandre Tkatchenko, Huziel E. Sauceda, Igor Poltavsky, Kristof T. Schütt, Klaus-Robert Müller

1611.04678

Global Optimization of Copper Clusters at the ZnO(10-10) Surface Using a DFT-based Neural Network Potential and Genetic Algorithms

Martín Leandro Paleico, Jörg Behler

2007.06459

ChemTS: An Efficient Python Library for de novo Molecular Generation

Xiufeng Yang, Jinzhe Zhang, Kazuki Yoshizoe, Kei Terayama, Koji Tsuda

1710.00616

Deep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanics

Linfeng Zhang, Jiequn Han, Han Wang, Roberto Car, Weinan E

1707.09571

Incorporating electronic information into Machine Learning potential energy surfaces via approaching the ground-state electronic energy as a function of atom-based electronic populations

Xiaowei Xie, Kristin A. Persson, David W. Small

2003.01893

Generating Focussed Molecule Libraries for Drug Discovery with Recurrent Neural Networks

Marwin H. S. Segler, Thierry Kogej, Christian Tyrchan, Mark P. Waller

1701.01329

Relevance of Rotationally Equivariant Convolutions for Predicting Molecular Properties

Benjamin Kurt Miller, Mario Geiger, Tess E. Smidt, Frank Noé

2008.08461

Unifying machine learning and quantum chemistry -- a deep neural network for molecular wavefunctions

K. T. Schütt, M. Gastegger, A. Tkatchenko, K. -R. Müller, R. J. Maurer

1906.10033

Reinforced dynamics for enhanced sampling in large atomic and molecular systems

Linfeng Zhang, Han Wang, Weinan E

1712.03461

Incorporating long-range physics in atomic-scale machine learning

Andrea Grisafi, Michele Ceriotti

1909.04512

A flexible and adaptive grid algorithm for global optimization utilizing basin hopping Monte Carlo

Martín Leandro Paleico, Jörg Behler

2002.00716

Machine Learning the Physical Non-Local Exchange-Correlation Functional of Density-Functional Theory

Jonathan Schmidt, Carlos L. Benavides-Riveros, Miguel A. L. Marques

1908.06198

An adaptive variational algorithm for exact molecular simulations on a quantum computer

Harper R. Grimsley, Sophia E. Economou, Edwin Barnes, Nicholas J. Mayhall

1812.11173

Machine learning for molecular simulation

Frank Noé, Alexandre Tkatchenko, Klaus-Robert Müller, Cecilia Clementi

1911.02792

Symmetry-Aware Actor-Critic for 3D Molecular Design

Gregor N. C. Simm, Robert Pinsler, Gábor Csányi, José Miguel Hernández-Lobato

2011.12747

Learning Neural Generative Dynamics for Molecular Conformation Generation

Minkai Xu, Shitong Luo, Yoshua Bengio, Jian Peng, Jian Tang

2102.10240

Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules

Johannes Gasteiger, Shankari Giri, Johannes T. Margraf, Stephan Günnemann

2011.14115

Solving Many-Electron Schrödinger Equation Using Deep Neural Networks

Jiequn Han, Linfeng Zhang, Weinan E

1807.07014

An accelerated linear method for optimizing non-linear wavefunctions in variational Monte Carlo

Iliya Sabzevari, Ankit Mahajan, Sandeep Sharma

1908.04423

Coarse Graining Molecular Dynamics with Graph Neural Networks

Brooke E. Husic, Nicholas E. Charron, Dominik Lemm, Jiang Wang, Adrià Pérez, Maciej Majewski, Andreas Krämer, Yaoyi Chen, Simon Olsson, Gianni de Fabritiis, Frank Noé, Cecilia Clementi

2007.11412