ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1606.00318
  4. Cited By
Discovering Phase Transitions with Unsupervised Learning
v1v2 (latest)

Discovering Phase Transitions with Unsupervised Learning

1 June 2016
Lei Wang
ArXiv (abs)PDFHTML

Papers citing "Discovering Phase Transitions with Unsupervised Learning"

50 / 86 papers shown
On the flow matching interpretability
On the flow matching interpretability
Francesco Pivi
Simone Gazza
Davide Evangelista
R. Amadini
M. Gabbrielli
162
0
0
24 Oct 2025
Attention to Order: Transformers Discover Phase Transitions via Learnability
Attention to Order: Transformers Discover Phase Transitions via Learnability
Şener Özönder
251
0
0
08 Oct 2025
Why is topology hard to learn?
Why is topology hard to learn?
D. O. Oriekhov
Stan Bergkamp
Guliuxin Jin
Juan Daniel Torres Luna
Badr Zouggari
Sibren van der Meer
Naoual El Yazidi
Eliska Greplova
PINNAI4CE
329
0
0
30 Sep 2025
Artificial intelligence for representing and characterizing quantum systems
Artificial intelligence for representing and characterizing quantum systems
Yuxuan Du
Yan Zhu
Y. Zhang
Min-hsiu Hsieh
Patrick Rebentrost
...
Ya-Dong Wu
Jens Eisert
G. Chiribella
Dacheng Tao
B. Sanders
216
4
0
05 Sep 2025
Machine Learning Workflow for Analysis of High-Dimensional Order Parameter Space: A Case Study of Polymer Crystallization from Molecular Dynamics Simulations
Machine Learning Workflow for Analysis of High-Dimensional Order Parameter Space: A Case Study of Polymer Crystallization from Molecular Dynamics Simulations
Elyar Tourani
Brian J. Edwards
Bamin Khomami
139
2
0
23 Jul 2025
Siamese Neural Network for Label-Efficient Critical Phenomena Prediction in 3D Percolation Models
Siamese Neural Network for Label-Efficient Critical Phenomena Prediction in 3D Percolation Models
Shanshan Wang
Dian Xu
Jianmin Shen
Feng Gao
Wei Li
Weibing Deng
127
0
0
05 Jul 2025
Uncovering Magnetic Phases with Synthetic Data and Physics-Informed Training
Uncovering Magnetic Phases with Synthetic Data and Physics-Informed Training
Agustin Medina
Marcelo Arlego
Carlos A. Lamas
AI4CE
201
0
0
15 May 2025
AI-Newton: A Concept-Driven Physical Law Discovery System without Prior Physical Knowledge
AI-Newton: A Concept-Driven Physical Law Discovery System without Prior Physical Knowledge
You-Le Fang
Dong-Shan Jian
Xiang Li
Yan Ma
310
2
0
02 Apr 2025
Interpretable Machine Learning in Physics: A Review
Interpretable Machine Learning in Physics: A Review
Sebastian Johann Wetzel
Seungwoong Ha
Raban Iten
Miriam Klopotek
Ziming Liu
AI4CE
437
17
0
30 Mar 2025
Learning phases with Quantum Monte Carlo simulation cell
Learning phases with Quantum Monte Carlo simulation cell
Amrita Ghosh
Mugdha Sarkar
Ying-Jer Kao
Pochung Chen
142
1
0
29 Mar 2025
Exploring the Energy Landscape of RBMs: Reciprocal Space Insights into Bosons, Hierarchical Learning and Symmetry Breaking
Exploring the Energy Landscape of RBMs: Reciprocal Space Insights into Bosons, Hierarchical Learning and Symmetry Breaking
J. Q. Toledo-Marín
Anindita Maiti
Geoffrey C. Fox
R. Melko
DRL
505
0
0
27 Mar 2025
Renormalization-Inspired Effective Field Neural Networks for Scalable Modeling of Classical and Quantum Many-Body Systems
Renormalization-Inspired Effective Field Neural Networks for Scalable Modeling of Classical and Quantum Many-Body Systems
Xi Liu
Yujun Zhao
Chun Yu Wan
Yang Zhang
Junwei Liu
316
0
0
24 Feb 2025
Phase Transitions in the Output Distribution of Large Language Models
Phase Transitions in the Output Distribution of Large Language Models
Julian Arnold
Flemming Holtorf
Frank Schafer
Niels Lörch
312
6
0
27 May 2024
Identifying phase transitions in physical systems with neural networks:
  a neural architecture search perspective
Identifying phase transitions in physical systems with neural networks: a neural architecture search perspective
R. C. Terin
Z. G. Arenas
Roberto Santana
260
1
0
23 Apr 2024
Advantage of Quantum Neural Networks as Quantum Information Decoders
Advantage of Quantum Neural Networks as Quantum Information Decoders
Weishun Zhong
O. Shtanko
R. Movassagh
153
2
0
11 Jan 2024
Machine learning in physics: a short guide
Machine learning in physics: a short guideEurophysics letters (EPL), 2023
F. A. Rodrigues
PINNAI4CE
331
14
0
16 Oct 2023
Inferring physical laws by artificial intelligence based causal models
Inferring physical laws by artificial intelligence based causal models
Jorawar Singh
Kishor Bharti
Arvind
CMLAI4CE
271
0
0
08 Sep 2023
Fluctuation based interpretable analysis scheme for quantum many-body
  snapshots
Fluctuation based interpretable analysis scheme for quantum many-body snapshotsSciPost Physics (SciPost Phys.), 2023
Henning Schlomer
A. Bohrdt
337
6
0
12 Apr 2023
Machine learning for structure-property relationships: Scalability and
  limitations
Machine learning for structure-property relationships: Scalability and limitationsPhysical Review E (PRE), 2023
Zhongzheng Tian
Sheng Zhang
Gia-Wei Chern
105
2
0
11 Apr 2023
Exponentially Improved Efficient and Accurate Machine Learning for
  Quantum Many-body States with Provable Guarantees
Exponentially Improved Efficient and Accurate Machine Learning for Quantum Many-body States with Provable GuaranteesPhysical Review Research (Phys. Rev. Res.), 2023
Yanming Che
C. Gneiting
Franco Nori
315
1
0
10 Apr 2023
Improved machine learning algorithm for predicting ground state
  properties
Improved machine learning algorithm for predicting ground state propertiesNature Communications (Nat. Commun.), 2023
Laura Lewis
Hsin-Yuan Huang
Viet-Trung Tran
Sebastian Lehner
R. Kueng
J. Preskill
AI4CE
238
65
0
30 Jan 2023
Data-driven identification and analysis of the glass transition in
  polymer melts
Data-driven identification and analysis of the glass transition in polymer meltsACS Macro Letters (ACS Macro Lett.), 2022
Atreyee Banerjee
H. Hsu
K. Kremer
O. Kukharenko
44
18
0
25 Nov 2022
Toward Unlimited Self-Learning MCMC with Parallel Adaptive Annealing
Toward Unlimited Self-Learning MCMC with Parallel Adaptive Annealing
Yuma Ichikawa
Akira Nakagawa
Hiromoto Masayuki
Yuhei Umeda
BDL
177
0
0
25 Nov 2022
Power-law Scaling to Assist with Key Challenges in Artificial
  Intelligence
Power-law Scaling to Assist with Key Challenges in Artificial IntelligenceScientific Reports (Sci Rep), 2020
Yuval Meir
Shira Sardi
Shiri Hodassman
Karin Kisos
Itamar Ben-Noam
A. Goldental
Ido Kanter
250
21
0
15 Nov 2022
Machine learning of percolation models using graph convolutional neural networks
Hua Tian
Li-Ru Zhang
Youjin Deng
Wanzhou Zhang
AI4CE
109
0
0
07 Jul 2022
Snake net and balloon force with a neural network for detecting multiple
  phases
Snake net and balloon force with a neural network for detecting multiple phasesPhysical Review E (Phys. Rev. E), 2022
Xiaodong Sun
Hui Yang
Na Wu
Tony C. Scott
Jie M. Zhang
Wanzhou Zhang
159
1
0
19 May 2022
A simple framework for contrastive learning phases of matter
A simple framework for contrastive learning phases of matterChinese Physics Letters (CPL), 2022
Xiaodong Han
Sheng-Song Xu
Zhen Feng
Rong-Qiang He
Zhong-Yi Lu
155
9
0
11 May 2022
Inferring topological transitions in pattern-forming processes with
  self-supervised learning
Inferring topological transitions in pattern-forming processes with self-supervised learningnpj Computational Materials (npj Comput. Mater.), 2022
M. Abram
Keith Burghardt
Greg Ver Steeg
Aram Galstyan
Rémi Dingreville
AI4CE
215
10
0
19 Mar 2022
A Group-Equivariant Autoencoder for Identifying Spontaneously Broken
  Symmetries
A Group-Equivariant Autoencoder for Identifying Spontaneously Broken SymmetriesPhysical Review E (Phys. Rev. E), 2022
Devanshu Agrawal
A. Del Maestro
Steven Johnston
James Ostrowski
DRLAI4CE
273
2
0
13 Feb 2022
Learning entanglement breakdown as a phase transition by confusion
Learning entanglement breakdown as a phase transition by confusionNew Journal of Physics (NJP), 2022
M. A. Gavreev
A. S. Mastiukova
E. Kiktenko
A. Fedorov
376
11
0
01 Feb 2022
Feature extraction of machine learning and phase transition point of
  Ising model
Feature extraction of machine learning and phase transition point of Ising model
S. Funai
181
3
0
22 Nov 2021
Generalization in quantum machine learning from few training data
Generalization in quantum machine learning from few training dataNature Communications (Nat Commun), 2021
Matthias C. Caro
Hsin-Yuan Huang
M. Cerezo
Kunal Sharma
A. Sornborger
L. Cincio
Patrick J. Coles
411
504
0
09 Nov 2021
Weighted Quantum Channel Compiling through Proximal Policy Optimization
Weighted Quantum Channel Compiling through Proximal Policy Optimization
Weiyuan Gong
Sicheng Jiang
D. Deng
145
2
0
03 Nov 2021
Quantitative analysis of phase transitions in two-dimensional XY models
  using persistent homology
Quantitative analysis of phase transitions in two-dimensional XY models using persistent homologyPhysical Review E (PRE), 2021
Nicholas Sale
Jeffrey Giansiracusa
B. Lucini
228
20
0
22 Sep 2021
Recent advances for quantum classifiers
Recent advances for quantum classifiersScience China Physics Mechanics and Astronomy (SCPMA), 2021
Weikang Li
D. Deng
AAML
341
104
0
30 Aug 2021
Direct detection of plasticity onset through total-strain profile
  evolution
Direct detection of plasticity onset through total-strain profile evolutionPHYSICAL REVIEW MATERIALS (PRM), 2021
Stefanos Papanikolaou
M. Alava
AI4CE
62
4
0
08 Jul 2021
Provably efficient machine learning for quantum many-body problems
Provably efficient machine learning for quantum many-body problems
Hsin-Yuan Huang
R. Kueng
Giacomo Torlai
Victor V. Albert
J. Preskill
AI4CE
426
301
0
23 Jun 2021
Variational Autoencoder Analysis of Ising Model Statistical
  Distributions and Phase Transitions
Variational Autoencoder Analysis of Ising Model Statistical Distributions and Phase Transitions
D. Yevick
DRL
288
7
0
13 Apr 2021
Can a CNN trained on the Ising model detect the phase transition of the
  $q$-state Potts model?
Can a CNN trained on the Ising model detect the phase transition of the qqq-state Potts model?
Kimihiko Fukushima
K. Sakai
269
13
0
08 Apr 2021
Quantum field-theoretic machine learning
Quantum field-theoretic machine learning
Dimitrios Bachtis
Gert Aarts
B. Lucini
AI4CE
235
33
0
18 Feb 2021
Universal Adversarial Examples and Perturbations for Quantum Classifiers
Universal Adversarial Examples and Perturbations for Quantum ClassifiersNational Science Review (NSR), 2021
Weiyuan Gong
D. Deng
AAML
271
42
0
15 Feb 2021
Machine-Learned Phase Diagrams of Generalized Kitaev Honeycomb Magnets
Machine-Learned Phase Diagrams of Generalized Kitaev Honeycomb MagnetsPhysical Review Research (Phys. Rev. Res.), 2021
N. Rao
Ke Liu
Marc Machaczek
L. Pollet
AI4CE
280
9
0
01 Feb 2021
Variational Neural Annealing
Variational Neural AnnealingNature Machine Intelligence (Nat. Mach. Intell.), 2021
Mohamed Hibat-Allah
E. Inack
R. Wiersema
R. Melko
Juan Carrasquilla
DRL
303
104
0
25 Jan 2021
Noise-Robust End-to-End Quantum Control using Deep Autoregressive Policy
  Networks
Noise-Robust End-to-End Quantum Control using Deep Autoregressive Policy NetworksMathematical and Scientific Machine Learning (MSML), 2020
Jiahao Yao
Paul Köttering
Hans Gundlach
Lin Lin
Marin Bukov
313
15
0
12 Dec 2020
Deep learning Local Reduced Density Matrices for Many-body Hamiltonian
  Estimation
Deep learning Local Reduced Density Matrices for Many-body Hamiltonian EstimationChinese Physics Letters (CPL), 2020
Xinran Ma
Z. C. Tu
Shi-Ju Ran
330
8
0
05 Dec 2020
Learning Order Parameters from Videos of Dynamical Phases for Skyrmions
  with Neural Networks
Learning Order Parameters from Videos of Dynamical Phases for Skyrmions with Neural NetworksPhysical Review Applied (PR Applied), 2020
Weidi Wang
Zeyuan Wang
Yinghui Zhang
Bo Sun
K. Xia
127
1
0
02 Dec 2020
Interpretable Phase Detection and Classification with Persistent
  Homology
Interpretable Phase Detection and Classification with Persistent Homology
A. Cole
Gregory J. Loges
G. Shiu
146
3
0
01 Dec 2020
Machine Learning approach to muon spectroscopy analysis
Machine Learning approach to muon spectroscopy analysis
T. Tula
G. Möller
Jorge Quintanilla
Sean Giblin
A. D. Hillier
E. E. McCabe
S. Ramos
D. S. Barker
S. Gibson
110
6
0
09 Oct 2020
Emergence of a finite-size-scaling function in the supervised learning
  of the Ising phase transition
Emergence of a finite-size-scaling function in the supervised learning of the Ising phase transitionJournal of Statistical Mechanics: Theory and Experiment (JSTAT), 2020
Dongkyu Kim
Dong-Hee Kim
LRM
248
4
0
01 Oct 2020
Restricted Boltzmann Machine Flows and The Critical Temperature of Ising
  models
Restricted Boltzmann Machine Flows and The Critical Temperature of Ising models
R. Veiga
R. Vicente
AI4CE
174
5
0
17 Jun 2020
12
Next
Page 1 of 2