Janosh Riebesell
- A foundation model for atomistic materials chemistry
2023/12/29 by Ilyes Batatia, Philipp Benner, Batatia, Ilyes +182 · 5 voices · 152 citations
Materials Science · Decision Sciences · #physics.chem-ph #cond-mat.mtrl-sci
- Matbench Discovery -- A framework to evaluate machine learning crystal stability predictions
2023/08/28 by Janosh Riebesell, Riebesell, Janosh, Rhys E. A. Goodall +13 · 18 citations
Computer Science · Materials Science · #Computational Drug Discovery Methods #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #X-ray Diffraction in Crystallography
- A Foundational Potential Energy Surface Dataset for Materials
2025/03/06 by Aaron D. Kaplan, Kaplan, Aaron D., Runze Liu +15 · 21 citations
Materials Science · Physics and Astronomy · Chemistry · #Machine Learning in Materials Science #Quantum many-body systems #Advanced Physical and Chemical Molecular Interactions
- LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and Distillation
2024/01/30 by Yuan Chiang, Chiang, Yuan, Chia-Hong Chou +4 · 10 citations
Materials Science · #Machine Learning in Materials Science #Electron and X-Ray Spectroscopy Techniques #X-ray Diffraction in Crystallography
- Atomate2: modular workflows for materials science
2025/01/01 by Alex M. Ganose, Hrushikesh Sahasrabuddhe, Mark Asta +53 · 2 voices · 11 citations
Chemical Engineering · Decision Sciences · Materials Science · #Catalysis and Oxidation Reactions #Machine Learning in Materials Science #Scientific Computing and Data Management
- Overcoming systematic softening in universal machine learning interatomic potentials by fine-tuning
2024/05/11 by Bowen Deng, Deng, Bowen, Yunyoung Choi +15 · 7 citations
Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Materials Science (cond-mat.mtrl-sci) #Neural Networks and Applications
- Atomate2: Modular workflows for materials science
2025/01/22 by Alex M. Ganose, Hrushikesh Sahasrabuddhe, Mark Asta +51 · 1 voice · 1 citation
Materials Science · #Machine Learning in Materials Science
- TorchSim: An efficient atomistic simulation engine in PyTorch
2025/08/08 by Orion Cohen, Janosh Riebesell, Cohen, Orion +14 · 3 citations
Biochemistry, Genetics and Molecular Biology · Materials Science · #Block Copolymer Self-Assembly #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #Protein Structure and Dynamics