Image de couverture de livre

A practical guide to machine learning interatomic potentials -- Status and future

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Jacobs, Ryan, Morgan, Dane, Attarian, Siamak, Meng, Jun, Shen, Chen, Wu, Zhenghao, Xie, Clare Yijia, Yang, Julia H., Artrith, Nongnuch, Blaiszik, Ben, Ceder, Gerbrand, Choudhary, Kamal, Csanyi, Gabor, Cubuk, Ekin Dogus, Deng, Bowen, Drautz, Ralf, Fu, Xiang, Godwin, Jonathan, Honavar, Vasant, Isayev, Olexandr, Johansson, Anders, Kozinsky, Boris, Martiniani, Stefano, Ong, Shyue Ping, Poltavsky, Igor, Schmidt, KJ, Takamoto, So, Thompson, Aidan, Westermayr, Julia, Wood, Brandon M.
Format:	Preprint
Publié:	2025
Sujets:	Materials Science Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Knowing when to trust machine-learned interatomic potentials
par: Mehdi, Shams, et autres
Publié: (2026)

Scaling (Down) CLIP: A Comprehensive Analysis of Data, Architecture, and Training Strategies
par: Li, Zichao, et autres
Publié: (2024)

Machine Learning Potential Powered Insights into the Mechanical Stability of Amorphous Li-Si Alloys
par: Wei, Zixiong, et autres
Publié: (2024)

Mechanistic Insights into the Oxygen Evolution Reaction on Nickel-Doped Barium Titanate via Machine Learning-Accelerated Simulations
par: Boonpalit, Kajjana, et autres
Publié: (2024)

Bayesian Neural Networks versus deep ensembles for uncertainty quantification in machine learning interatomic potentials
par: Farris, Riccardo, et autres
Publié: (2025)

Studies of Ni-Cr complexation in FLiBe molten salt using machine learning interatomic potentials
par: Attarian, Siamak, et autres
Publié: (2024)

Modeling phase transformations in Mn-rich disordered rocksalt cathodes with machine learning interatomic potentials
par: Zhong, Peichen, et autres
Publié: (2025)

Hyperdimensional Cross-Modal Alignment of Frozen Language and Image Models for Efficient Image Captioning
par: Dalvi, Abhishek, et autres
Publié: (2026)

Hyperdimensional Representation Learning for Node Classification and Link Prediction
par: Dalvi, Abhishek, et autres
Publié: (2024)

Cross-functional transferability in universal machine learning interatomic potentials
par: Huang, Xu, et autres
Publié: (2025)

Force field optimization by end-to-end differentiable atomistic simulation
par: Gangan, Abhijeet S., et autres
Publié: (2024)

Search for thermodynamically stable ambient-pressure superconducting hydrides in GNoME database
par: Sanna, Antonio, et autres
Publié: (2025)

Highly Antioxidative Lithium Salt Enables High-Voltage Ether Electrolyte for Lithium Metal Battery
par: He, Jian, et autres
Publié: (2024)

EsaCL: Efficient Continual Learning of Sparse Models
par: Ren, Weijieying, et autres
Publié: (2024)

Conservative adaptive-precision interatomic potentials
par: Immel, David, et autres
Publié: (2025)

Machine learning for smell: Ordinal odor strength prediction of molecular perfumery components
par: Fichtelmann, Peter, et autres
Publié: (2025)

Reinforcement learning for traversing chemical structure space: Optimizing transition states and minimum energy paths of molecules
par: Barrett, Rhyan, et autres
Publié: (2023)

Causal Effect Estimation Using Random Hyperplane Tessellations
par: Dalvi, Abhishek, et autres
Publié: (2024)

C-HDNet: Hyperdimensional Computing for Causal Effect Estimation from Observational Data Under Network Interference
par: Dalvi, Abhishek, et autres
Publié: (2025)

Graph atomic cluster expansion for foundational machine learning interatomic potentials
par: Lysogorskiy, Yury, et autres
Publié: (2025)

Applications of Modular Co-Design for De Novo 3D Molecule Generation
par: Reidenbach, Danny, et autres
Publié: (2025)

Scalable Diffusion for Materials Generation
par: Yang, Sherry, et autres
Publié: (2023)

Thermodynamic accessibility of Li-Mn-Ti-O cation disordered rock-salt phases
par: Kam, Ronald L., et autres
Publié: (2026)

Overcoming systematic softening in universal machine learning interatomic potentials by fine-tuning
par: Deng, Bowen, et autres
Publié: (2024)

3M-Diffusion: Latent Multi-Modal Diffusion for Language-Guided Molecular Structure Generation
par: Zhu, Huaisheng, et autres
Publié: (2024)

Computational search for materials having a giant anomalous Hall effect in the pyrochlore and spinel crystal structures
par: Sullivan, Sean, et autres
Publié: (2025)

Anticipating the Selectivity of Intramolecular Cyclization Reaction Pathways with Neural Network Potentials
par: Casetti, Nicholas, et autres
Publié: (2025)

GEOM-Drugs Revisited: Toward More Chemically Accurate Benchmarks for 3D Molecule Generation
par: Nikitin, Filipp, et autres
Publié: (2025)

Excited-state nonadiabatic dynamics in explicit solvent using machine learned interatomic potentials
par: Tiefenbacher, Maximilian X., et autres
Publié: (2025)

Deep Learning within Tabular Data: Foundations, Challenges, Advances and Future Directions
par: Ren, Weijieying, et autres
Publié: (2025)

Projection-Free Transformers via Gaussian Kernel Attention
par: Kundu, Debarshi, et autres
Publié: (2026)

Transferable excited-state dynamics enable screening of fluorescent protein chromophores
par: Barrett, Rhyan, et autres
Publié: (2026)

Transferable Machine Learning Potential X-MACE for Excited States using Integrated DeepSets
par: Barrett, Rhyan, et autres
Publié: (2025)

Hierarchical generative modeling for the design of multi-component systems
par: Barrett, Rhyan, et autres
Publié: (2026)

Mechanisms of alkali ionic transport in amorphous oxyhalides solid state conductors
par: Binci, Luca, et autres
Publié: (2026)

DistMLIP: A Distributed Inference Platform for Machine Learning Interatomic Potentials
par: Han, Kevin, et autres
Publié: (2025)

Li+/H+ exchange in solid-state oxide Li-ion conductors
par: Li, Zhuohan, et autres
Publié: (2025)

Hierarchical high-throughput screening of alkaline-stable lithium-ion conductors combining machine learning and first-principles calculations
par: Li, Zhuohan, et autres
Publié: (2025)

MolBind: Multimodal Alignment of Language, Molecules, and Proteins
par: Xiao, Teng, et autres
Publié: (2024)

Restoring the Sweet Spot: Pass-Rate Weighted Self-Distillation for LLM Reasoning
par: Liu, Zehao, et autres
Publié: (2026)