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Limited Data Rolling Bearing Fault Diagnosis With Few-Shot Learning

IEEE access, 2019, Vol.7, p.110895-110904

2019

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Inverse design of composite metal oxide optical materials based on deep transfer learning and global optimization

Computational materials science, 2021-02, Vol.188, p.110166, Article 110166

2021

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Mlatticeabc: Generic Lattice Constant Prediction of Crystal Materials Using Machine Learning

ACS omega, 2021-05, Vol.6 (17), p.11585-11594

2021

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Machine Learning-Based Prediction of Crystal Systems and Space Groups from Inorganic Materials Compositions

ACS omega, 2020-02, Vol.5 (7), p.3596-3606

2020

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Scalable deeper graph neural networks for high-performance materials property prediction

Patterns (New York, N.Y.), 2022-05, Vol.3 (5), p.100491-100491, Article 100491

2022

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Critical Temperature Prediction of Superconductors Based on Atomic Vectors and Deep Learning

Symmetry (Basel), 2020-02, Vol.12 (2), p.262

2020

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Computational Prediction of Critical Temperatures of Superconductors Based on Convolutional Gradient Boosting Decision Trees

IEEE access, 2020, Vol.8, p.57868-57878

2020

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Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study

npj computational materials, 2024-07, Vol.10 (1), p.144-14, Article 144

2024

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Discovery of 2D Materials using Transformer Network‐Based Generative Design

Advanced intelligent systems, 2023-12, Vol.5 (12), p.n/a

2023

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Material transformers: deep learning language models for generative materials design

Machine learning: science and technology, 2023-03, Vol.4 (1), p.15001

2023

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Composition based crystal materials symmetry prediction using machine learning with enhanced descriptors

Computational materials science, 2021-10, Vol.198, p.110686, Article 110686

2021

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Generative Design of Inorganic Compounds Using Deep Diffusion Language Models

The journal of physical chemistry. A, Molecules, spectroscopy, kinetics, environment, & general theory, 2024-07

2024

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Global Mapping of Structures and Properties of Crystal Materials

Journal of chemical information and modeling, 2023-06, Vol.63 (12), p.3814-3826

2023

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Chaos analysis and stability control of the MEMS resonator via the type-2 sequential FNN

Microsystem technologies : sensors, actuators, systems integration, 2021, Vol.27 (1), p.173-182

2021

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Crystal structure prediction of materials with high symmetry using differential evolution

Journal of physics. Condensed matter, 2021-11, Vol.33 (45), p.455902

2021

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TCSP: a Template-Based Crystal Structure Prediction Algorithm for Materials Discovery

Inorganic chemistry, 2022-06, Vol.61 (22), p.8431-8439

2022

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DeepXRD, a Deep Learning Model for Predicting XRD spectrum from Material Composition

ACS applied materials & interfaces, 2022-09, Vol.14 (35), p.40102-40115

2022

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Realistic material property prediction using domain adaptation based machine learning

Digital discovery, 2024-02, Vol.3 (2), p.3-312

2024

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Effect of repeated Kangaroo Mother Care on repeated procedural pain in preterm infants: A randomized controlled trial

International journal of nursing studies, 2015-07, Vol.52 (7), p.1157-1165

2015

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Computational Screening of New Perovskite Materials Using Transfer Learning and Deep Learning

Applied sciences, 2019-12, Vol.9 (24), p.5510

2019

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Contact map based crystal structure prediction using global optimization

CrystEngComm, 2021-03, Vol.23 (8), p.1765-1776

2021

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Handbook of Evolutionary Machine Learning

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Deep Learning-Based Prediction of Contact Maps and Crystal Structures of Inorganic Materials

ACS omega, 2023-07, Vol.8 (29), p.26170-26179

2023

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Venus round trip using solar sail

Science China. Physics, mechanics & astronomy, 2012-08, Vol.55 (8), p.1485-1499

2012

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Evolutionary Machine Learning in Science and Engineering

Handbook of Evolutionary Machine Learning, p.535-561

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Limited Data Rolling Bearing Fault Diagnosis With Few-Shot Learning

Inverse design of composite metal oxide optical materials based on deep transfer learning and global optimization

Mlatticeabc: Generic Lattice Constant Prediction of Crystal Materials Using Machine Learning

Machine Learning-Based Prediction of Crystal Systems and Space Groups from Inorganic Materials Compositions

Scalable deeper graph neural networks for high-performance materials property prediction

Critical Temperature Prediction of Superconductors Based on Atomic Vectors and Deep Learning

Computational Prediction of Critical Temperatures of Superconductors Based on Convolutional Gradient Boosting Decision Trees

Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study

Discovery of 2D Materials using Transformer Network‐Based Generative Design

Material transformers: deep learning language models for generative materials design

Composition based crystal materials symmetry prediction using machine learning with enhanced descriptors

Generative Design of Inorganic Compounds Using Deep Diffusion Language Models

Global Mapping of Structures and Properties of Crystal Materials

Chaos analysis and stability control of the MEMS resonator via the type-2 sequential FNN

Crystal structure prediction of materials with high symmetry using differential evolution

TCSP: a Template-Based Crystal Structure Prediction Algorithm for Materials Discovery

DeepXRD, a Deep Learning Model for Predicting XRD spectrum from Material Composition

Realistic material property prediction using domain adaptation based machine learning

Effect of repeated Kangaroo Mother Care on repeated procedural pain in preterm infants: A randomized controlled trial

Computational Screening of New Perovskite Materials Using Transfer Learning and Deep Learning

Contact map based crystal structure prediction using global optimization

Handbook of Evolutionary Machine Learning

Deep Learning-Based Prediction of Contact Maps and Crystal Structures of Inorganic Materials

Venus round trip using solar sail

Evolutionary Machine Learning in Science and Engineering

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