3.6k citations · 10.6k across the 54 of their papers we have counts for
5 papers · 1 filter
dPV: An End-to-End Differentiable Solar-Cell Simulator
Sean Mann, Eric Fadel, Samuel S. Schoenholz +3
We introduce dPV, an end-to-end differentiable photovoltaic (PV) cell simulator based on the drift-diffusion model and Beer-Lambert law for optical absorption. dPV is programmed in…
Self-assembling kinetics: Accessing a new design space via differentiable statistical-physics models
Carl P. Goodrich, Ella M. King, Samuel S. Schoenholz +2
The inverse problem of designing component interactions to target emergent structure is fundamental to numerous applications in biotechnology, materials science, and statistical ph…
Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics
Li Li, Stephan Hoyer, Ryan Pederson +4
Including prior knowledge is important for effective machine learning models in physics, and is usually achieved by explicitly adding loss terms or constraints on model architectur…
JAX, M.D.: A Framework for Differentiable Physics
Samuel S. Schoenholz, Ekin D. Cubuk
We introduce JAX MD, a software package for performing differentiable physics simulations with a focus on molecular dynamics. JAX MD includes a number of physics simulation environ…
Accelerated search and design of stretchable graphene kirigami using machine learning
Paul Z. Hanakata, Ekin D. Cubuk, David K. Campbell +1
Making kirigami-inspired cuts into a sheet has been shown to be an effective way of designing stretchable materials with metamorphic properties where the 2D shape can transform int…