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Fast, accurate, and transferable many-body interatomic potentials by
  symbolic regression
v1v2v3 (latest)

Fast, accurate, and transferable many-body interatomic potentials by symbolic regression

1 April 2019
Alberto Hernandez
Adarsh Balasubramanian
Fenglin Yuan
Simon Mason
Tim Mueller
ArXiv (abs)PDFHTML

Papers citing "Fast, accurate, and transferable many-body interatomic potentials by symbolic regression"

18 / 18 papers shown
Title
SyMANTIC: An Efficient Symbolic Regression Method for Interpretable and Parsimonious Model Discovery in Science and Beyond
SyMANTIC: An Efficient Symbolic Regression Method for Interpretable and Parsimonious Model Discovery in Science and Beyond
Madhav Muthyala
Farshud Sorourifar
You Peng
J. Paulson
281
2
0
05 Feb 2025
Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$
Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large ppp
Shengbin Ye
Meng Li
113
0
0
17 Oct 2024
Symbolic Regression with a Learned Concept Library
Symbolic Regression with a Learned Concept Library
Arya Grayeli
Atharva Sehgal
Omar Costilla-Reyes
Miles Cranmer
Swarat Chaudhuri
111
15
0
14 Sep 2024
Discovering Nuclear Models from Symbolic Machine Learning
Discovering Nuclear Models from Symbolic Machine Learning
Jose M. Munoz
S. Udrescu
Ronald F. Garcia Ruiz
109
0
0
17 Apr 2024
Multi-View Symbolic Regression
Multi-View Symbolic Regression
E. Russeil
Fabrício Olivetti de França
K. Malanchev
Bogdan Burlacu
E. Ishida
Marion Leroux
Clément Michelin
Guillaume Moinard
E. Gangler
28
1
0
06 Feb 2024
LTAU-FF: Loss Trajectory Analysis for Uncertainty in Atomistic Force
  Fields
LTAU-FF: Loss Trajectory Analysis for Uncertainty in Atomistic Force Fields
Joshua A. Vita
Amit Samanta
Fei Zhou
Vincenzo Lordi
68
3
0
01 Feb 2024
Interpretable Ensemble Learning for Materials Property Prediction with
  Classical Interatomic Potentials: Carbon as an Example
Interpretable Ensemble Learning for Materials Property Prediction with Classical Interatomic Potentials: Carbon as an Example
Xinyu Jiang
Haofan Sun
K. Choudhary
H. Zhuang
Qiong Nian
13
0
0
24 Jul 2023
Controllable Neural Symbolic Regression
Controllable Neural Symbolic Regression
Tommaso Bendinelli
Luca Biggio
Pierre-Alexandre Kamienny
79
15
0
20 Apr 2023
Interpretable Symbolic Regression for Data Science: Analysis of the 2022
  Competition
Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition
F. O. França
M. Virgolin
M. Kommenda
M. Majumder
M. Cranmer
...
Bogdan Burlacu
Jaan Kasak
Meera Machado
Casper Wilstrup
William La Cava
51
10
0
03 Apr 2023
Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search
Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search
Pierre-Alexandre Kamienny
Guillaume Lample
Sylvain Lamprier
M. Virgolin
117
32
0
22 Feb 2023
Online Symbolic Regression with Informative Query
Online Symbolic Regression with Informative Query
Pengwei Jin
Di Huang
Rui Zhang
Xingui Hu
Ziyuan Nan
Zidong Du
Qi Guo
Yunji Chen
60
2
0
21 Feb 2023
Incorporating Background Knowledge in Symbolic Regression using a
  Computer Algebra System
Incorporating Background Knowledge in Symbolic Regression using a Computer Algebra System
Charles Fox
Neil Tran
Nikki Nacion
Samiha Sharlin
Tyler R. Josephson
124
3
0
27 Jan 2023
Interpretable Scientific Discovery with Symbolic Regression: A Review
Interpretable Scientific Discovery with Symbolic Regression: A Review
N. Makke
Sanjay Chawla
129
116
0
20 Nov 2022
Generalizability of Functional Forms for Interatomic Potential Models
  Discovered by Symbolic Regression
Generalizability of Functional Forms for Interatomic Potential Models Discovered by Symbolic Regression
Alberto Hernandez
Tim Mueller
40
1
0
27 Oct 2022
Symbolic Regression is NP-hard
Symbolic Regression is NP-hard
M. Virgolin
S. Pissis
157
64
0
03 Jul 2022
Symbolic Regression in Materials Science: Discovering Interatomic
  Potentials from Data
Symbolic Regression in Materials Science: Discovering Interatomic Potentials from Data
Bogdan Burlacu
M. Kommenda
G. Kronberger
Stephan M. Winkler
M. Affenzeller
34
4
0
13 Jun 2022
Evolving symbolic density functionals
Evolving symbolic density functionals
He Ma
Arunachalam Narayanaswamy
Patrick F. Riley
Li Li
142
32
0
03 Mar 2022
Polymer Informatics: Current Status and Critical Next Steps
Polymer Informatics: Current Status and Critical Next Steps
Lihua Chen
G. Pilania
Rohit Batra
T. D. Huan
Chiho Kim
Christopher Kuenneth
R. Ramprasad
AI4CE
80
185
0
01 Nov 2020
1