Search Results for author: Shravan Veerapaneni

Found 7 papers, 3 papers with code

Scalable neural quantum states architecture for quantum chemistry

no code implementations11 Aug 2022 Tianchen Zhao, James Stokes, Shravan Veerapaneni

Variational optimization of neural-network representations of quantum states has been successfully applied to solve interacting fermionic problems.

Numerical and geometrical aspects of flow-based variational quantum Monte Carlo

no code implementations28 Mar 2022 James Stokes, Brian Chen, Shravan Veerapaneni

This article aims to summarize recent and ongoing efforts to simulate continuous-variable quantum systems using flow-based variational quantum Monte Carlo techniques, focusing for pedagogical purposes on the example of bosons in the field amplitude (quadrature) basis.

Continuous-variable neural-network quantum states and the quantum rotor model

1 code implementation15 Jul 2021 James Stokes, Saibal De, Shravan Veerapaneni, Giuseppe Carleo

We initiate the study of neural-network quantum state algorithms for analyzing continuous-variable lattice quantum systems in first quantization.

Quantization Variational Monte Carlo

Meta Variational Monte Carlo

no code implementations20 Nov 2020 Tianchen Zhao, James Stokes, Oliver Knitter, Brian Chen, Shravan Veerapaneni

An identification is found between meta-learning and the problem of determining the ground state of a randomly generated Hamiltonian drawn from a known ensemble.

Meta-Learning Variational Monte Carlo

Natural evolution strategies and variational Monte Carlo

1 code implementation9 May 2020 Tianchen Zhao, Giuseppe Carleo, James Stokes, Shravan Veerapaneni

A notion of quantum natural evolution strategies is introduced, which provides a geometric synthesis of a number of known quantum/classical algorithms for performing classical black-box optimization.

Combinatorial Optimization Variational Monte Carlo

An Active Learning Framework for Constructing High-fidelity Mobility Maps

no code implementations7 Mar 2020 Gary R. Marple, David Gorsich, Paramsothy Jayakumar, Shravan Veerapaneni

A mobility map, which provides maximum achievable speed on a given terrain, is essential for path planning of autonomous ground vehicles in off-road settings.

Active Learning BIG-bench Machine Learning +2

A unified integral equation scheme for doubly-periodic Laplace and Stokes boundary value problems in two dimensions

2 code implementations24 Nov 2016 Alex H. Barnett, Gary Marple, Shravan Veerapaneni, Lin Zhao

We present a spectrally-accurate scheme to turn a boundary integral formulation for an elliptic PDE on a single unit cell geometry into one for the fully periodic problem.

Numerical Analysis 65N38, 65N80, 76D07, 76M50

Cannot find the paper you are looking for? You can Submit a new open access paper.