研飞ivySCI (青藤学术）

Machine Learning: Science and Technology

短名	Mach. Learn.: Sci. Technol.
Journal Impact	6.35
国际分区	MULTIDISCIPLINARY SCIENCES(Q1)
期刊索引	SCI Q1中科院 2 区

ISSN	2632-2153
h-index	31
国内分区	物理与天体物理(2区)物理与天体物理计算机人工智能(2区)物理与天体物理综合性期刊(2区)物理与天体物理计算机跨学科应用(3区)

期刊主页

涉及主题	计算机科学人工智能数学机器学习物理量子力学算法工程类人工神经网络统计程序设计语言生物化学哲学心理学操作系统计算机视觉
出版信息	出版商: Institute of Physics Publishing，出版周期: ，期刊类型: journal
基本数据	创刊年份: 2020，原创研究文献占比: ，自引率:， Gold OA占比: 99.36

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专利引用格式

Machine learning stochastic differential equations for the evolution of order parameters of classical many-body systems in and out of equilibrium

2024-9-13

Multi-fidelity Gaussian process surrogate modeling for regression problems in physics

2024-9-13

Accelerating cavity fault prediction using deep learning at Jefferson laboratory

2024-9-13

WBC-KICNet: Knowledge-infused convolutional neural network for white blood cell classification

2024-9-12

LoGAN: Local generative adversarial network for novel structure prediction

2024-9-12

Equivariant tensor network potentials

2024-9-11

Uncovering obscured phonon dynamics from powder inelastic neutron scattering using machine learning

2024-9-11

Robust Anomaly Detection for Particle Physics Using Multi-Background Representation Learning

2024-9-6

Optimizing ZX-Diagrams with Deep Reinforcement Learning

2024-9-3

DiffLense: A Conditional Diffusion Model for Super-Resolution of Gravitational Lensing Data

2024-9-3

Simultaneous energy and mass calibration of large-radius jets with the ATLAS detector using a deep neural network

2024-9-1

Triggering dark showers with conditional dual auto-encoders

2024-9-1

Designing quantum multi-category classifier from the perspective of brain processing information

2024-8-29

Planning with tensor networks based on active inference

2024-8-29

Data-Driven Acceleration of Multi-Physics Simulations

2024-8-29

Photonic modes prediction via Multi-Modal Diffusion model

2024-8-27

An exponential reduction in training data sizes for machine learning derived entanglement witnesses

2024-8-27

Transforming the bootstrap: using Transformers to compute scattering amplitudes in planar N = 4 Super Yang-Mills theory

2024-8-27

Active Causal Learning for Decoding Chemical Complexities with Targeted Interventions

2024-8-23

Improving model robustness to weight noise via consistency regularization

2024-8-23

Learning on the correctness class for domain inverse problems of gravimetry

2024-8-22

Leveraging normalizing flows for orbital-free density functional theory

2024-8-21

Accelerating Scientific Discovery with Generative Knowledge Extraction, Graph-Based Representation, and Multimodal Intelligent Graph Reasoning

2024-8-21

SemiH: DFT Hamiltonian neural network training with semi-supervised learning

2024-8-21

Identifying chaotic dynamics in noisy time series through multimodal deep neural networks

2024-8-20

Regulating the development of accurate data-driven physics-informed deformation models

2024-8-20

A Combined Modeling Method for Complex Multi-Fidelity Data Fusion

2024-8-20

Neural force functional for non-equilibrium many-body colloidal systems

2024-8-20

Evaluating Cell Growth and Hypoxic Regions of 3D Spheroids <i>via</i> a Machine Learning Approach

2024-8-20

Towards a comprehensive visualisation of structure in large scale data sets

2024-8-15

Benchmarking machine learning interatomic potentials via phonon anharmonicity

2024-8-14

Virtual reality for understanding artificial-intelligence-driven scientific discovery with an application in quantum optics

2024-8-13

JefiAtten: An Attention-Based Neural Network Model for Solving Maxwell's Equations with Charge and Current Sources

2024-8-13

Concept Graph Embedding Models for Enhanced Accuracy and Interpretability

2024-8-13

Chaotic attractor reconstruction using small reservoirs - the inﬂuence of topology

2024-8-13

Transfer learning with generative models for object detection on limited datasets

2024-8-12

Data-driven sparse modeling of oscillations in plasma space propulsion

2024-8-8

Normalizing flows as an enhanced sampling method for atomistic supercooled liquids

2024-8-7

Formation energy prediction of neutral single-atom impurities in 2D materials using tree-based machine learning

2024-8-7

DISCOVERING SYMBOLIC LAWS DIRECTLY FROM TRAJECTORIES WITH HAMILTONIAN GRAPH NEURAL NETWORKS

2024-8-6

Trainability issues in quantum policy gradients

2024-8-6

Coincidence Anomaly Detection for Unsupervised Locating of Edge Localized Modes in the DIII-D Tokamak Dataset

2024-8-6

Quantum support vector data description for anomaly detection

2024-8-6

Molecular relaxation by reverse diffusion with time step prediction

2024-8-6

Background suppression for volcano muography with machine learning

2024-8-2

OmniJet-α: the first cross-task foundation model for particle physics

2024-8-2

ArtiSAN: Navigating the complexity of material structures with deep reinforcement learning

2024-8-1

Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning

2024-8-1

Physics-Informed Neural Network for Turbulent Flow Reconstruction in Composite Porous-Fluid Systems

2024-7-31

Negative order Sobolev cubatures: preconditioners of partial differential equation learning tasks circumventing numerical stiffness

2024-7-30

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Machine Learning: Science and Technology

期刊引文格式

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专利引用格式

最新文章

Machine learning stochastic differential equations for the evolution of order parameters of classical many-body systems in and out of equilibrium

Multi-fidelity Gaussian process surrogate modeling for regression problems in physics

Accelerating cavity fault prediction using deep learning at Jefferson laboratory

WBC-KICNet: Knowledge-infused convolutional neural network for white blood cell classification

LoGAN: Local generative adversarial network for novel structure prediction

Equivariant tensor network potentials

Uncovering obscured phonon dynamics from powder inelastic neutron scattering using machine learning

Robust Anomaly Detection for Particle Physics Using Multi-Background Representation Learning

Optimizing ZX-Diagrams with Deep Reinforcement Learning

DiffLense: A Conditional Diffusion Model for Super-Resolution of Gravitational Lensing Data

Simultaneous energy and mass calibration of large-radius jets with the ATLAS detector using a deep neural network

Triggering dark showers with conditional dual auto-encoders

Designing quantum multi-category classifier from the perspective of brain processing information

Planning with tensor networks based on active inference

Data-Driven Acceleration of Multi-Physics Simulations

Photonic modes prediction via Multi-Modal Diffusion model

An exponential reduction in training data sizes for machine learning derived entanglement witnesses

Transforming the bootstrap: using Transformers to compute scattering amplitudes in planar N = 4 Super Yang-Mills theory

Active Causal Learning for Decoding Chemical Complexities with Targeted Interventions

Improving model robustness to weight noise via consistency regularization

Learning on the correctness class for domain inverse problems of gravimetry

Leveraging normalizing flows for orbital-free density functional theory

Accelerating Scientific Discovery with Generative Knowledge Extraction, Graph-Based Representation, and Multimodal Intelligent Graph Reasoning

SemiH: DFT Hamiltonian neural network training with semi-supervised learning

Identifying chaotic dynamics in noisy time series through multimodal deep neural networks

Regulating the development of accurate data-driven physics-informed deformation models

A Combined Modeling Method for Complex Multi-Fidelity Data Fusion

Neural force functional for non-equilibrium many-body colloidal systems

Evaluating Cell Growth and Hypoxic Regions of 3D Spheroids <i>via</i> a Machine Learning Approach

Towards a comprehensive visualisation of structure in large scale data sets

Benchmarking machine learning interatomic potentials via phonon anharmonicity

Virtual reality for understanding artificial-intelligence-driven scientific discovery with an application in quantum optics

JefiAtten: An Attention-Based Neural Network Model for Solving Maxwell's Equations with Charge and Current Sources

Concept Graph Embedding Models for Enhanced Accuracy and Interpretability

Chaotic attractor reconstruction using small reservoirs - the inﬂuence of topology

Transfer learning with generative models for object detection on limited datasets

Data-driven sparse modeling of oscillations in plasma space propulsion

Normalizing flows as an enhanced sampling method for atomistic supercooled liquids

Formation energy prediction of neutral single-atom impurities in 2D materials using tree-based machine learning

DISCOVERING SYMBOLIC LAWS DIRECTLY FROM TRAJECTORIES WITH HAMILTONIAN GRAPH NEURAL NETWORKS

Trainability issues in quantum policy gradients

Coincidence Anomaly Detection for Unsupervised Locating of Edge Localized Modes in the DIII-D Tokamak Dataset

Quantum support vector data description for anomaly detection

Molecular relaxation by reverse diffusion with time step prediction

Background suppression for volcano muography with machine learning

OmniJet-α: the first cross-task foundation model for particle physics

ArtiSAN: Navigating the complexity of material structures with deep reinforcement learning

Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning

Physics-Informed Neural Network for Turbulent Flow Reconstruction in Composite Porous-Fluid Systems

Negative order Sobolev cubatures: preconditioners of partial differential equation learning tasks circumventing numerical stiffness

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