Search Results for author:
Found 3 papers, 3 papers with code
Natural Quantum Monte Carlo Computation of Excited States
We present a variational Monte Carlo algorithm for estimating the lowest excited states of a quantum system which is a natural generalization of the estimation of ground states.
A Self-Attention Ansatz for Ab-initio Quantum Chemistry
In recent years, deep neural networks like the FermiNet and PauliNet have been used to significantly improve the accuracy of these first-principle calculations, but they lack an attention-like mechanism for gating interactions between electrons.
Solving Mixed Integer Programs Using Neural Networks
Our approach constructs two corresponding neural network-based components, Neural Diving and Neural Branching, to use in a base MIP solver such as SCIP.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
