Machine|learning interatomic potentials

Machine Learning Interatomic Potential Development with MAML

In this talk at NanoHUB's Hands-on Data Science and Machine Learning Training Series, Yunxing Zuo from the Materials Virtual Lab discusses ...

Robust training of machine learning interatomic potentials with ...

Abstract Machine learning interatomic potentials (MLIPs) enable accurate simulations of materials at scales beyond that accessible by ab initio methods and ...

Machine Learning Classical Interatomic Potentials for Molecular ...

Fingerprint. Dive into the research topics of 'Machine Learning Classical Interatomic Potentials for Molecular Dynamics from First-Principles ...

Evaluation of Machine Learning Interatomic Potentials for Gold ...

We analyse the efficacy of machine learning (ML) interatomic potentials (IP) in modelling gold (Au) nanoparticles.

Machine-learning models of matter beyond interatomic potentials

Combining electronic structure calculations and machine learning (ML) techniques has become a common approach in the atomistic modeling of ...

Designing efficient, interpretable, and generalizable machine ...

Interatomic potentials (IPs) are invaluable tools in the fields of computational materials science and chemistry for their ability to accelerate atomic-scale ...

Developing a machine-learned interatomic potential for molecular ...

In the last decade, machine learning (ML) methods have demonstrated impressive performances in predicting accurate values for energy and forces ...

Open Datasets and Deep Learning Interatomic Potentials ... - Aionics

Abstract: Machine learning accelerated catalyst discovery efforts have seen much progress in the last few years. Datasets of computational ...

From Machine-Learning Interatomic Potentials to Materials Chemistry

Novel interatomic potentials based on machine learning (ML) have recently garnered a lot of attention in computational physics, chemistry, and ...

Shyue Ping Ong on LinkedIn: Robust Training of Machine Learning ...

Shyue Ping Ong's Post · Robust Training of Machine Learning Interatomic Potentials with Dimensionality Reduction and Stratified Sampling · Explore ...

Ju Li, "A Universal Empirical Interatomic Potential" - YouTube

0:00 Introduction · 4:23 Machine Learning Interatomic Potentials Gaussian approximation potential (GAP), moment tensor potentials (MTP), neural ...

GULP use machine learning interatomic potential

GULP use machine learning interatomic potential ... Dear Prof. Julian,. The empirical force field can address the most of issues, but it sometimes ...

Webinar 118 | Machine learning interatomic potentials for ... - YouTube

The webinar titled "Machine Learning Interatomic Potentials for Modelling Radiation Damage" features Professor Kai Nordlund from the ...

Exploring the necessary complexity of interatomic potentials

The application of machine learning models and algorithms towards describing atomic interactions has been a major area of interest in materials simulations ...

Machine Learning Trains Atomic Potentials Needed to Accelerate ...

Interatomic potentials established from low-computational cost ML models trained with expensive quantum mechanics calculations offer a highly ...

Gabor Csányi - Machine learning potentials - YouTube

Recorded 17 April 2023. Gabor Csányi of the University of Cambridge presents "Machine learning potentials: from polynomials to message ...

Day 2 - Learning ML Interatomic Potentials | Gianni De Fabritiis

Join Portal to connect with the speakers: https://portal.valencelabs.com/ This is a recording from the 2024 Machine Learning for Drug ...

Machine-Learning Potentials: Introduction and Examples ... - YouTube

In this talk I will present recent work on machine learned energy functionals, which can be used to predict energies, forces and molecular ...

Convenient and efficient development of Machine Learning ...

2021.01. · This tutorial introduces the concepts of machine learning interatomic potentials (ML-IAPs) in materials science, including two ...

NVIDIA ALCHEMI: Pioneering AI-Driven Material Discovery

ALCHEMI introduces machine learning interatomic potentials (MLIPs) that provide a cost-effective and accurate method for predicting material ...