More recently, I have been using #MachineLearning tools to develop #InteratomicPotentials:
doi.org/10.1103/Phys...
This work developed an MLIP for the prototypical austenitic #StainlessSteel, Fe-Cr-Ni. Potentials such as this will help to accelerate future simulations 🚀
doi.org/10.1103/Phys...
This work developed an MLIP for the prototypical austenitic #StainlessSteel, Fe-Cr-Ni. Potentials such as this will help to accelerate future simulations 🚀
Collinear-spin machine learned interatomic potential for ${\mathrm{Fe}}_{7}{\mathrm{Cr}}_{2}\mathrm{Ni}$ alloy
We have developed a machine learned interatomic potential for the prototypical austenitic steel ${\mathrm{Fe}}_{7}{\mathrm{Cr}}_{2}\mathrm{Ni}$, using the Gaussian approximation potential (GAP) framew...
doi.org
January 3, 2025 at 10:02 AM
More recently, I have been using #MachineLearning tools to develop #InteratomicPotentials:
doi.org/10.1103/Phys...
This work developed an MLIP for the prototypical austenitic #StainlessSteel, Fe-Cr-Ni. Potentials such as this will help to accelerate future simulations 🚀
doi.org/10.1103/Phys...
This work developed an MLIP for the prototypical austenitic #StainlessSteel, Fe-Cr-Ni. Potentials such as this will help to accelerate future simulations 🚀
Paul Cuillier et al.: Integrating machine learning interatomic potentials with hybrid reverse Monte Carlo structure refinements in RMCProfile ##ReverseMonteCarlo##MachineLearning##InteratomicPotentials@OhioState...##IUCrhttps://journals.iucr.org/paper?S1600576724009282
Integrating machine learning interatomic potentials with hybrid reverse Monte Carlo structure refinements in RMCProfile
New software capabilities in RMCProfile allow researchers to study the structure of materials by combining machine learning interatomic potentials and reverse Monte Carlo.
journals.iucr.org
October 30, 2024 at 1:00 AM
Paul Cuillier et al.: Integrating machine learning interatomic potentials with hybrid reverse Monte Carlo structure refinements in RMCProfile ##ReverseMonteCarlo##MachineLearning##InteratomicPotentials@OhioState...##IUCrhttps://journals.iucr.org/paper?S1600576724009282
Join us today at #NeurIPS2024 for our poster presentation:
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
🗓️ When: Wed, Dec 11, 11 a.m. – 2 p.m. PST
📍 Where: East Exhibit Hall A-C, Poster #4107
#MachineLearning #InteratomicPotentials #Equivariance #GraphNeuralNetworks
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
🗓️ When: Wed, Dec 11, 11 a.m. – 2 p.m. PST
📍 Where: East Exhibit Hall A-C, Poster #4107
#MachineLearning #InteratomicPotentials #Equivariance #GraphNeuralNetworks
📣 Can we go beyond state-of-the-art message-passing models based on spherical tensors such as #MACE and #NequIP?
Our #NeurIPS2024 paper explores higher-rank irreducible Cartesian tensors to design equivariant #MLIPs.
Paper: arxiv.org/abs/2405.14253
Code: github.com/nec-research...
Our #NeurIPS2024 paper explores higher-rank irreducible Cartesian tensors to design equivariant #MLIPs.
Paper: arxiv.org/abs/2405.14253
Code: github.com/nec-research...
December 11, 2024 at 3:38 PM
Join us today at #NeurIPS2024 for our poster presentation:
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
🗓️ When: Wed, Dec 11, 11 a.m. – 2 p.m. PST
📍 Where: East Exhibit Hall A-C, Poster #4107
#MachineLearning #InteratomicPotentials #Equivariance #GraphNeuralNetworks
Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
🗓️ When: Wed, Dec 11, 11 a.m. – 2 p.m. PST
📍 Where: East Exhibit Hall A-C, Poster #4107
#MachineLearning #InteratomicPotentials #Equivariance #GraphNeuralNetworks