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By-passing the Kohn-Sham equations with machine learning
v1v2v3 (latest)

By-passing the Kohn-Sham equations with machine learning

9 September 2016
Felix Brockherde
Leslie Vogt
Li Li
M. Tuckerman
K. Burke
K. Müller
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "By-passing the Kohn-Sham equations with machine learning"

50 / 88 papers shown
Title
Predicting fermionic densities using a Projected Quantum Kernel method
Predicting fermionic densities using a Projected Quantum Kernel method
Francesco Perciavalle
Francesco Plastina
Michele Pisarra
Nicola Lo Gullo
139
0
0
18 Apr 2025
Machine learning-guided construction of an analytic kinetic energy functional for orbital free density functional theory
Machine learning-guided construction of an analytic kinetic energy functional for orbital free density functional theory
Sergei Manzhos
Johann Luder
Manabu Ihara
Manabu Ihara
116
0
0
08 Feb 2025
E3STO: Orbital Inspired SE(3)-Equivariant Molecular Representation for
  Electron Density Prediction
E3STO: Orbital Inspired SE(3)-Equivariant Molecular Representation for Electron Density Prediction
Ilan Mitnikov
Joseph Jacobson
90
0
0
08 Oct 2024
Machine learning approach for vibronically renormalized electronic band
  structures
Machine learning approach for vibronically renormalized electronic band structures
Niraj Aryal
Sheng Zhang
Weiguo Yin
Gia-Wei Chern
150
0
0
03 Sep 2024
Accelerating Electron Dynamics Simulations through Machine Learned Time
  Propagators
Accelerating Electron Dynamics Simulations through Machine Learned Time Propagators
Karan Shah
A. Cangi
AI4CE
112
1
0
12 Jul 2024
NeuralSCF: Neural network self-consistent fields for density functional
  theory
NeuralSCF: Neural network self-consistent fields for density functional theory
Feitong Song
Ji Feng
70
1
0
22 Jun 2024
A Recipe for Charge Density Prediction
A Recipe for Charge Density Prediction
Xiang Fu
Andrew S. Rosen
Kyle Bystrom
Rui Wang
Albert Musaelian
Boris Kozinsky
Tess E. Smidt
Tommi Jaakkola
94
6
0
29 May 2024
3DReact: Geometric deep learning for chemical reactions
3DReact: Geometric deep learning for chemical reactions
Puck van Gerwen
K. Briling
Charlotte Bunne
Vignesh Ram Somnath
Rubén Laplaza
Andreas Krause
C. Corminboeuf
3DV
86
8
0
13 Dec 2023
Higher-Order Equivariant Neural Networks for Charge Density Prediction
  in Materials
Higher-Order Equivariant Neural Networks for Charge Density Prediction in Materials
Teddy Koker
Keegan Quigley
Eric Taw
Kevin Tibbetts
Lin Li
68
15
0
08 Dec 2023
Alpha Zero for Physics: Application of Symbolic Regression with Alpha
  Zero to find the analytical methods in physics
Alpha Zero for Physics: Application of Symbolic Regression with Alpha Zero to find the analytical methods in physics
Yoshihiro Michishita
AI4CE
85
2
0
21 Nov 2023
Equivariant Neural Operator Learning with Graphon Convolution
Equivariant Neural Operator Learning with Graphon Convolution
Chaoran Cheng
Jian-wei Peng
45
5
0
17 Nov 2023
Degeneration of kernel regression with Matern kernels into low-order
  polynomial regression in high dimension
Degeneration of kernel regression with Matern kernels into low-order polynomial regression in high dimension
Sergei Manzhos
Manabu Ihara
90
8
0
17 Nov 2023
Electronic excited states from physically-constrained machine learning
Electronic excited states from physically-constrained machine learning
Edoardo Cignoni
Divya Suman
Jigyasa Nigam
Lorenzo Cupellini
B. Mennucci
Michele Ceriotti
63
17
0
01 Nov 2023
Machine learning for accuracy in density functional approximations
Machine learning for accuracy in density functional approximations
Johannes Voss
AI4CE
44
3
0
01 Nov 2023
Towards Combinatorial Generalization for Catalysts: A Kohn-Sham
  Charge-Density Approach
Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach
Phillip Pope
David Jacobs
59
3
0
28 Oct 2023
Overcoming the Barrier of Orbital-Free Density Functional Theory for
  Molecular Systems Using Deep Learning
Overcoming the Barrier of Orbital-Free Density Functional Theory for Molecular Systems Using Deep Learning
He Zhang
Siyuan Liu
Jiacheng You
Chang-Shu Liu
Shuxin Zheng
Ziheng Lu
Tong Wang
Nanning Zheng
Jia Zhang
77
22
0
28 Sep 2023
Grad DFT: a software library for machine learning enhanced density
  functional theory
Grad DFT: a software library for machine learning enhanced density functional theory
Pablo Antonio Moreno Casares
Jack S. Baker
Matija Medvidović
Roberto Dos Reis
J. M. Arrazola
100
9
0
23 Sep 2023
Physics-inspired Equivariant Descriptors of Non-bonded Interactions
Physics-inspired Equivariant Descriptors of Non-bonded Interactions
Kevin K. Huguenin-Dumittan
P. Loche
Haoran Ni
Michele Ceriotti
30
22
0
25 Aug 2023
Materials Informatics: An Algorithmic Design Rule
Materials Informatics: An Algorithmic Design Rule
B. Bishnoi
58
0
0
05 May 2023
Wigner kernels: body-ordered equivariant machine learning without a
  basis
Wigner kernels: body-ordered equivariant machine learning without a basis
Filippo Bigi
Sergey Pozdnyakov
Michele Ceriotti
54
16
0
07 Mar 2023
SchNetPack 2.0: A neural network toolbox for atomistic machine learning
SchNetPack 2.0: A neural network toolbox for atomistic machine learning
Kristof T. Schütt
Stefaan S. P. Hessmann
Niklas W. A. Gebauer
Jonas Lederer
M. Gastegger
78
65
0
11 Dec 2022
The loss of the property of locality of the kernel in high-dimensional
  Gaussian process regression on the example of the fitting of molecular
  potential energy surfaces
The loss of the property of locality of the kernel in high-dimensional Gaussian process regression on the example of the fitting of molecular potential energy surfaces
Sergei Manzhos
Manabu Ihara
GP
18
6
0
21 Nov 2022
Embed and Emulate: Learning to estimate parameters of dynamical systems
  with uncertainty quantification
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification
Ruoxi Jiang
Rebecca Willett
61
7
0
03 Nov 2022
Accelerating hypersonic reentry simulations using deep learning-based
  hybridization (with guarantees)
Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees)
Paul Novello
Gaël Poëtte
D. Lugato
S. Peluchon
P. Congedo
AI4CE
71
8
0
27 Sep 2022
A machine learning approach to predict the structural and magnetic
  properties of Heusler alloy families
A machine learning approach to predict the structural and magnetic properties of Heusler alloy families
S. Mitra
Aquil Ahmad
Sajib Biswas
A. Das
27
16
0
07 Aug 2022
Molecular-orbital-based Machine Learning for Open-shell and
  Multi-reference Systems with Kernel Addition Gaussian Process Regression
Molecular-orbital-based Machine Learning for Open-shell and Multi-reference Systems with Kernel Addition Gaussian Process Regression
Lixue Cheng
Jiace Sun
J. E. Deustua
Vignesh C. Bhethanabotla
Thomas F. Miller
39
7
0
17 Jul 2022
Electronic-structure properties from atom-centered predictions of the
  electron density
Electronic-structure properties from atom-centered predictions of the electron density
Andrea Grisafi
Alan M Lewis
M. Rossi
Michele Ceriotti
90
20
0
28 Jun 2022
Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian
  Process Regression with Derivatives in Molecular-orbital-based Machine
  Learning
Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-orbital-based Machine Learning
Jiace Sun
Lixue Cheng
Thomas F. Miller
74
3
0
31 May 2022
Machine Learning Diffusion Monte Carlo Energies
Machine Learning Diffusion Monte Carlo Energies
Kevin Ryczko
J. Krogel
Isaac Tamblyn
DiffM
29
14
0
09 May 2022
Putting Density Functional Theory to the Test in
  Machine-Learning-Accelerated Materials Discovery
Putting Density Functional Theory to the Test in Machine-Learning-Accelerated Materials Discovery
Chenru Duan
Fan Liu
Aditya Nandy
Heather J. Kulik
AI4CE
39
34
0
06 May 2022
Accurate Molecular-Orbital-Based Machine Learning Energies via
  Unsupervised Clustering of Chemical Space
Accurate Molecular-Orbital-Based Machine Learning Energies via Unsupervised Clustering of Chemical Space
Lixue Cheng
Jiace Sun
Thomas F. Miller
48
13
0
21 Apr 2022
DiffMD: A Geometric Diffusion Model for Molecular Dynamics Simulations
DiffMD: A Geometric Diffusion Model for Molecular Dynamics Simulations
Fang Wu
Stan Z. Li
DiffM
60
33
0
19 Apr 2022
Evolving symbolic density functionals
Evolving symbolic density functionals
He Ma
Arunachalam Narayanaswamy
Patrick F. Riley
Li Li
142
32
0
03 Mar 2022
Prediction of the electron density of states for crystalline compounds
  with Atomistic Line Graph Neural Networks (ALIGNN)
Prediction of the electron density of states for crystalline compounds with Atomistic Line Graph Neural Networks (ALIGNN)
Prathik R. Kaundinya
K. Choudhary
S. Kalidindi
41
29
0
20 Jan 2022
Descriptors for Machine Learning Model of Generalized Force Field in
  Condensed Matter Systems
Descriptors for Machine Learning Model of Generalized Force Field in Condensed Matter Systems
Puhan Zhang
Sheng Zhang
Gia-Wei Chern
AI4CE
36
11
0
03 Jan 2022
Machine learning nonequilibrium electron forces for adiabatic spin
  dynamics
Machine learning nonequilibrium electron forces for adiabatic spin dynamics
Puhan Zhang
Gia-Wei Chern
42
16
0
22 Dec 2021
Equivariant graph neural networks for fast electron density estimation
  of molecules, liquids, and solids
Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solids
Peter Bjørn Jørgensen
Arghya Bhowmik
52
37
0
01 Dec 2021
Reducing the Long Tail Losses in Scientific Emulations with Active
  Learning
Reducing the Long Tail Losses in Scientific Emulations with Active Learning
Yi Heng Lim
M. F. Kasim
39
0
0
15 Nov 2021
Audacity of huge: overcoming challenges of data scarcity and data
  quality for machine learning in computational materials discovery
Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery
Aditya Nandy
Chenru Duan
Heather J. Kulik
AI4CE
131
47
0
02 Nov 2021
How Well Does Kohn-Sham Regularizer Work for Weakly Correlated Systems?
How Well Does Kohn-Sham Regularizer Work for Weakly Correlated Systems?
Bhupalee Kalita
Ryan Pederson
Jielun Chen
Li Li
K. Burke
108
9
0
28 Oct 2021
Geometric Transformer for End-to-End Molecule Properties Prediction
Geometric Transformer for End-to-End Molecule Properties Prediction
Yoni Choukroun
Lior Wolf
AI4CEViT
78
16
0
26 Oct 2021
Deep learning for surrogate modelling of 2D mantle convection
Deep learning for surrogate modelling of 2D mantle convection
Siddhant Agarwal
Nicola Tosi
Pan Kessel
D. Breuer
G. Montavon
AI4TSAI4CE
72
8
0
23 Aug 2021
SE(3)-equivariant prediction of molecular wavefunctions and electronic
  densities
SE(3)-equivariant prediction of molecular wavefunctions and electronic densities
Oliver T. Unke
Mihail Bogojeski
M. Gastegger
Mario Geiger
Tess E. Smidt
Klaus-Robert Muller
86
94
0
04 Jun 2021
Learning the exchange-correlation functional from nature with fully
  differentiable density functional theory
Learning the exchange-correlation functional from nature with fully differentiable density functional theory
M. F. Kasim
S. Vinko
174
69
0
08 Feb 2021
Bayesian neural networks for weak solution of PDEs with uncertainty
  quantification
Bayesian neural networks for weak solution of PDEs with uncertainty quantification
Xiaoxuan Zhang
K. Garikipati
AI4CE
86
12
0
13 Jan 2021
On the equivalence of molecular graph convolution and molecular wave
  function with poor basis set
On the equivalence of molecular graph convolution and molecular wave function with poor basis set
Masashi Tsubaki
T. Mizoguchi
31
9
0
16 Nov 2020
Quantum deep field: data-driven wave function, electron density
  generation, and atomization energy prediction and extrapolation with machine
  learning
Quantum deep field: data-driven wave function, electron density generation, and atomization energy prediction and extrapolation with machine learning
Masashi Tsubaki
T. Mizoguchi
55
37
0
16 Nov 2020
Uncertainty estimation for molecular dynamics and sampling
Uncertainty estimation for molecular dynamics and sampling
G. Imbalzano
Yongbin Zhuang
V. Kapil
K. Rossi
Edgar A. Engel
Federico Grasselli
Michele Ceriotti
38
5
0
10 Nov 2020
DeepDFT: Neural Message Passing Network for Accurate Charge Density
  Prediction
DeepDFT: Neural Message Passing Network for Accurate Charge Density Prediction
Peter Bjørn Jørgensen
Arghya Bhowmik
38
22
0
04 Nov 2020
Machine learning of solvent effects on molecular spectra and reactions
Machine learning of solvent effects on molecular spectra and reactions
M. Gastegger
Kristof T. Schütt
Klaus-Robert Muller
AI4CE
61
62
0
28 Oct 2020
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