A classical density functional from machine learning and a convolutional neural network

A classical density functional from machine learning and a convolutional neural network

We use machine learning methods to approximate a classical density functional. As a study case, we choose the model problem of a Lennard Jones fluid in one dimension where there is no exact solution available and training data sets must be obtained from simulations. After separating the excess fr...

Full description

Bibliographic Details
Main Author:	Shang-Chun Lin, Martin Oettel
Format:	Article
Language:	English
Published:	SciPost 2019-02-01
Series:	SciPost Physics
Online Access:	https://scipost.org/SciPostPhys.6.2.025

Similar Items

From Classical Machine Learning to Deep Neural Networks: A Simplified Scientometric Review
by: Ravil I. Mukhamediev, et al.
Published: (2021-06-01)

Classical and Neural Network Machine Learning to Determine the Risk of Marijuana Use
by: Laura Zoboroski, et al.
Published: (2021-07-01)

Indian Classical Dance Action Identification and Classification with Convolutional Neural Networks
by: P. V. V. Kishore, et al.
Published: (2018-01-01)

An Improved Convolutional Neural Network on Crowd Density Estimation
by: Pan Shao-Yun, et al.
Published: (2016-01-01)

Microcalcification Detection in Mammogram Based on Traditional Machine Learning and Convolutional Neural Networks
by: HUANG, SHENG-CHI, et al.
Published: (2018)

Cerebral Microbleed Detection via Convolutional Neural Network and Extreme Learning Machine
by: Siyuan Lu, et al.
Published: (2021-09-01)

Recognition of industrial machine parts based on transfer learning with convolutional neural network.
by: Qiaoyang Li, et al.
Published: (2021-01-01)

An Enhanced Deep Convolutional Neural Network for Classifying Indian Classical Dance Forms
by: Nikita Jain, et al.
Published: (2021-07-01)

Image Classification, Deep Learning and Convolutional Neural Networks : A Comparative Study of Machine Learning Frameworks
by: Airola, Rasmus, et al.
Published: (2017)

Low-Rank Deep Convolutional Neural Network for Multitask Learning
by: Fang Su, et al.
Published: (2019-01-01)

Detecting exoplanets with machine learning : A comparative study between convolutional neural networks and support vector machines
by: Tiensuu, Jacob, et al.
Published: (2019)

Evaluation of Different Machine Learning Methods and Deep-Learning Convolutional Neural Networks for Landslide Detection
by: Omid Ghorbanzadeh, et al.
Published: (2019-01-01)

Automatic Electron Density Determination by Using a Convolutional Neural Network
by: Tatsuhito Hasegawa, et al.
Published: (2019-01-01)

Transferability of a Convolutional Neural Network (CNN) to Measure Traffic Density
by: Jiyong Chung, et al.
Published: (2021-05-01)

Compressing Convolutional Neural Networks by Pruning Density Peak Filters
by: Yunseok Jang, et al.
Published: (2021-01-01)

Automatic classification of mice vocalizations using Machine Learning techniques and Convolutional Neural Networks.
by: Marika Premoli, et al.
Published: (2021-01-01)

Learning an Efficient Convolution Neural Network for Pansharpening
by: Yecai Guo, et al.
Published: (2019-01-01)

Curriculum Learning with Deep Convolutional Neural Networks
by: Avramova, Vanya
Published: (2015)

Progressive Convolutional Neural Network for Incremental Learning
by: Zahid Ali Siddiqui, et al.
Published: (2021-08-01)

Convolutional Neural Network Based on Extreme Learning Machine for Maritime Ships Recognition in Infrared Images
by: Atmane Khellal, et al.
Published: (2018-05-01)

Machine Learning Applications of Convolutional Neural Networks and Unet Architecture to Predict and Classify Demosponge Behavior
by: Dominica Harrison, et al.
Published: (2021-09-01)

Machine learning transferable physics-based force fields using graph convolutional neural networks
by: Harris, William H.(William Hunt)
Published: (2021)

Year-Independent Prediction of Food Insecurity Using Classical and Neural Network Machine Learning Methods
by: Cade Christensen, et al.
Published: (2021-05-01)

Analysis and Comparison of Convolution Layer in Deep Convolution Neural Network
by: Yi-Chun Hu, et al.
Published: (2018)

A Configurable Architecture for Running Hybrid Convolutional Neural Networks in Low-Density FPGAs
by: Mario P. Vestias, et al.
Published: (2020-01-01)

From Audio to Topics: Learning Semantics with Convolutional Neural Network
by: Siao-Yun Dai, et al.
Published: (2017)

Classification of Heart Sounds Using Convolutional Neural Network
by: Fan Li, et al.
Published: (2020-06-01)

A Study of M-Learning Using Convolutional Neural Network
by: Pin-Sheng Fu, et al.
Published: (2018)

A primer on deep learning and convolutional neural networks for clinicians
by: Lara Lloret Iglesias, et al.
Published: (2021-08-01)

A New Improved Learning Algorithm for Convolutional Neural Networks
by: Jie Yang, et al.
Published: (2020-03-01)

A Study of OWA Operators Learned in Convolutional Neural Networks
by: Iris Dominguez-Catena, et al.
Published: (2021-08-01)

Woven Fabric Density Measurement by Using Multi-Scale Convolutional Neural Networks
by: Shuo Meng, et al.
Published: (2019-01-01)

Crowd Counting Method Based on Convolutional Neural Network With Global Density Feature
by: Zhi Liu, et al.
Published: (2019-01-01)

Efficiency of machine learning algorithms and convolutional neural network for detection of pathological changes in MR images of the brain
by: Julia Agafonova, et al.
Published: (2020-04-01)

The Study on Recognizing Learning Emotion with the Convolution Neural Networks
by: Zheng-De Wu, et al.
Published: (2017)

Adaptive learning cost‐sensitive convolutional neural network
by: Yun Hou, et al.
Published: (2021-08-01)

Learning in Convolutional Neural Networks Accelerated by Transfer Entropy
by: Adrian Moldovan, et al.
Published: (2021-09-01)

DNA Sequences Analysis of Single-Gene Disorders and Prediction Model Construction Based on Machine Learning and Convolutional Neural Networks
by: Min-Chen Lin, et al.
Published: (2019)

Improving Convolutional Neural Networks with Competitive Activation Function
by: Yao Ying, et al.
Published: (2021-01-01)

Transfer learning in hybrid classical-quantum neural networks
by: Andrea Mari, et al.
Published: (2020-10-01)