Neural Network Reparametrization for Accelerated Optimization in Molecular Simulations
- Nima Dehmamy
- Csaba Both
- et al.
- 2024
- NeurIPS 2024
Bio
Nima Dehmamy is a Research Staff Member at IBM Research, Cambridge MA. His research focuses on AI for science, equivariant networks, optimization theory and graph neural networks. His recent projects include
- Symmetries, conserved quantities and flat minima in the loss landscape
- Generative adversarial symmetry discovery
- Coarse-graining in machine learning models
He earned his PhD in physics from Boston University in 2016. He was a research faculty at Northwestern University 2019-2022.
Publications
Symmetry-Informed Governing Equation Discovery
- Jianke Yang
- Wang Rao
- et al.
- 2024
- NeurIPS 2024
Latent Space Symmetry Discovery
- Jianke Yang
- Nima Dehmamy
- et al.
- 2024
- ICML 2024
Hessian Reparametrization for Coarse-grained Energy Minimization
- Nima Dehmamy
- Csaba Both
- et al.
- 2024
- ICLR 2024
Understanding Mode Connectivity via Parameter Space Symmetry
- Bo Zhao
- Nima Dehmamy
- et al.
- 2023
- NeurIPS 2023
Coarse-graining via reparametrization avoids force matching and back-mapping
- Nima Dehmamy
- Csaba Both
- et al.
- 2023
- NeurIPS 2023
Latent Space Symmetry Discovery
- Jianke Yang
- Nima Dehmamy
- et al.
- 2023
- ICML 2023
Symmetries, flat minima, and the conserved quantities of gradient flow
- Bo Zhao
- Iordan Ganev
- et al.
- 2023
- ICLR 2023
Vox2Net: From 3D Shapes to Network Sculptures
- Nima Dehmamy
- Luca Stornaiuolo
- et al.
- 2018
- NeurIPS 2018
Top collaborators
SD
Subhro Das
Research Staff Member, Master Inventor
MM
Mauro Martino
Principal Research Staff Member and Manager, Visual AI Lab