Saved in:
| Main Authors: | Fu, Nihang, Wei, Lai, Hu, Jianjun |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.05223 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Improving realistic material property prediction using domain adaptation based machine learning
by: Hu, Jeffrey, et al.
Published: (2023)
by: Hu, Jeffrey, et al.
Published: (2023)
Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study
by: Omee, Sadman Sadeed, et al.
Published: (2024)
by: Omee, Sadman Sadeed, et al.
Published: (2024)
Physical Encoding Improves OOD Performance in Deep Learning Materials Property Prediction
by: Fu, Nihang, et al.
Published: (2024)
by: Fu, Nihang, et al.
Published: (2024)
TCSP 2.0: Template Based Crystal Structure Prediction with Improved Oxidation State Prediction and Chemistry Heuristics
by: Wei, Lai, et al.
Published: (2025)
by: Wei, Lai, et al.
Published: (2025)
Out-of-distribution materials property prediction using adversarial learning based fine-tuning
by: Li, Qinyang, et al.
Published: (2024)
by: Li, Qinyang, et al.
Published: (2024)
AlphaCrystal-II: Distance matrix based crystal structure prediction using deep learning
by: Song, Yuqi, et al.
Published: (2024)
by: Song, Yuqi, et al.
Published: (2024)
Data-Driven Topological Analysis of Polymorphic Crystal Structures
by: Dey, Sourin, et al.
Published: (2025)
by: Dey, Sourin, et al.
Published: (2025)
Facet: highly efficient E(3)-equivariant networks for interatomic potentials
by: Miklaucic, Nicholas, et al.
Published: (2025)
by: Miklaucic, Nicholas, et al.
Published: (2025)
CSPBench: a benchmark and critical evaluation of Crystal Structure Prediction
by: Wei, Lai, et al.
Published: (2024)
by: Wei, Lai, et al.
Published: (2024)
Self-supervised learning for crystal property prediction via denoising
by: New, Alexander, et al.
Published: (2024)
by: New, Alexander, et al.
Published: (2024)
Machine learning for structure-guided materials and process design
by: Morand, Lukas, et al.
Published: (2023)
by: Morand, Lukas, et al.
Published: (2023)
In context learning Foundation models for Materials Property Prediction with Small datasets
by: Li, Qinyang, et al.
Published: (2025)
by: Li, Qinyang, et al.
Published: (2025)
Low dimensional fragment-based descriptors for property predictions in inorganic materials with machine learning
by: Islam, Md Mohaiminul
Published: (2024)
by: Islam, Md Mohaiminul
Published: (2024)
Accurate prediction of structural and mechanical properties on amorphous materials enabled through machine-learning potentials: a case study of silicon nitride
by: Nayak, Ganesh Kumar, et al.
Published: (2024)
by: Nayak, Ganesh Kumar, et al.
Published: (2024)
Cross-scale covariance for material property prediction
by: Jasperson, Benjamin A., et al.
Published: (2024)
by: Jasperson, Benjamin A., et al.
Published: (2024)
Crystal Composition Transformer: Self‐Learning Neural Language Model for Generative and Tinkering Design of Materials
by: Lai Wei, et al.
Published: (2024)
by: Lai Wei, et al.
Published: (2024)
Machine learning assisted prediction of organic salt structure properties
by: Shapera, Ethan P., et al.
Published: (2024)
by: Shapera, Ethan P., et al.
Published: (2024)
A foundation machine learning potential with polarizable long-range interactions for materials modelling
by: Gao, Rongzhi, et al.
Published: (2024)
by: Gao, Rongzhi, et al.
Published: (2024)
Polymorphism Crystal Structure Prediction with Adaptive Space Group Diversity Control
by: Omee, Sadman Sadeed, et al.
Published: (2025)
by: Omee, Sadman Sadeed, et al.
Published: (2025)
Physics-informed Hamiltonian learning for large-scale optoelectronic property prediction
by: Schwade, Martin, et al.
Published: (2025)
by: Schwade, Martin, et al.
Published: (2025)
Transformer-based prediction of two-dimensional material electronic properties under elastic strain engineering
by: Ma, Haoran, et al.
Published: (2026)
by: Ma, Haoran, et al.
Published: (2026)
Enhancing composition-based materials property prediction by cross-modal knowledge transfer
by: Rubtsov, Ivan, et al.
Published: (2025)
by: Rubtsov, Ivan, et al.
Published: (2025)
Electronic and structural properties of group IV materials and their polytypes
by: Ziembicki, Jakub, et al.
Published: (2024)
by: Ziembicki, Jakub, et al.
Published: (2024)
Establishing Deep InfoMax as an effective self-supervised learning methodology in materials informatics
by: Moran, Michael, et al.
Published: (2024)
by: Moran, Michael, et al.
Published: (2024)
A dual-cutoff machine-learned potential for condensed organic systems obtained via uncertainty-guided active learning
by: Kahle, Leonid, et al.
Published: (2024)
by: Kahle, Leonid, et al.
Published: (2024)
Crystal structure prediction with host-guided inpainting generation and foundation potentials
by: Zhong, Peichen, et al.
Published: (2025)
by: Zhong, Peichen, et al.
Published: (2025)
Materials Properties Prediction (MAPP): Empowering the prediction of material properties solely based on chemical formulas
by: Xue, Si-Da, et al.
Published: (2023)
by: Xue, Si-Da, et al.
Published: (2023)
Large Berry curvature effects induced by extended nodal structures: Rational design strategy and high-throughput materials predictions
by: Wang, Wencheng, et al.
Published: (2025)
by: Wang, Wencheng, et al.
Published: (2025)
Optimal pre-train/fine-tune strategies for accurate material property predictions
by: Devi, Reshma, et al.
Published: (2024)
by: Devi, Reshma, et al.
Published: (2024)
Virp: neural network-accelerated prediction of physical properties in site-disordered materials
by: Chen, Andy Paul, et al.
Published: (2026)
by: Chen, Andy Paul, et al.
Published: (2026)
Machine learning method to determine concentrations of structural defects in irradiated materials
by: Johnson, Landon, et al.
Published: (2025)
by: Johnson, Landon, et al.
Published: (2025)
Machine learning for predicting ultralow thermal conductivity and high ZT in complex thermoelectric materials
by: Hao, Yuzhou, et al.
Published: (2024)
by: Hao, Yuzhou, et al.
Published: (2024)
Feature-based prediction of properties of cross-linked epoxy polymers by molecular dynamics and machine learning techniques
by: S., Sindu B., et al.
Published: (2023)
by: S., Sindu B., et al.
Published: (2023)
CAST: Cross Attention based multimodal fusion of Structure and Text for materials property prediction
by: Lee, Jaewan, et al.
Published: (2025)
by: Lee, Jaewan, et al.
Published: (2025)
Machine learning for structure-property relationships: Scalability and limitations
by: Tian, Zhongzheng, et al.
Published: (2023)
by: Tian, Zhongzheng, et al.
Published: (2023)
Deep learning generative model for crystal structure prediction
by: Luo, Xiaoshan, et al.
Published: (2024)
by: Luo, Xiaoshan, et al.
Published: (2024)
Accurate and efficient predictions of keyhole dynamics in laser materials processing using machine learning-aided simulations
by: Zhang, Jiahui, et al.
Published: (2024)
by: Zhang, Jiahui, et al.
Published: (2024)
Machine learning interatomic potential for predicting the thermal properties of uranium nitride
by: Chen, Beihan, et al.
Published: (2025)
by: Chen, Beihan, et al.
Published: (2025)
Self-supervised feature distillation and design of experiments for efficient training of micromechanical deep learning surrogates
by: Fernandez-Zelaia, Patxi, et al.
Published: (2024)
by: Fernandez-Zelaia, Patxi, et al.
Published: (2024)
Machine learning analysis of structural data to predict electronic properties in near-surface InAs quantum wells
by: Strohbeen, Patrick J., et al.
Published: (2024)
by: Strohbeen, Patrick J., et al.
Published: (2024)
Similar Items
-
Improving realistic material property prediction using domain adaptation based machine learning
by: Hu, Jeffrey, et al.
Published: (2023) -
Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study
by: Omee, Sadman Sadeed, et al.
Published: (2024) -
Physical Encoding Improves OOD Performance in Deep Learning Materials Property Prediction
by: Fu, Nihang, et al.
Published: (2024) -
TCSP 2.0: Template Based Crystal Structure Prediction with Improved Oxidation State Prediction and Chemistry Heuristics
by: Wei, Lai, et al.
Published: (2025) -
Out-of-distribution materials property prediction using adversarial learning based fine-tuning
by: Li, Qinyang, et al.
Published: (2024)