activity
20212026
most citedNetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems

147 citations · 210 across the 5 of their papers we have counts for

collaborators

5 papers

physics.chem-ph2026

Variational low-energy subspaces for chemically accurate excited states

Clemens Giuliani, Rocco Martinazzo, Giuseppe Carleo +1

Accurate electronic excited states are essential for photochemistry, spectroscopy and non-adiabatic molecular dynamics, but high-level calculations often scale steeply and require…

physics.chem-ph2025

Precise Quantum Chemistry calculations with few Slater Determinants

Clemens Giuliani, Jannes Nys, Rocco Martinazzo +2

Slater determinants have underpinned quantum chemistry for nearly a century, yet their full potential has remained challenging to exploit. In this work, we show that a variational…

quant-ph2023★ 51 cited

Unbiasing time-dependent Variational Monte Carlo by projected quantum evolution

Alessandro Sinibaldi, Clemens Giuliani, Giuseppe Carleo +1

We analyze the accuracy and sample complexity of variational Monte Carlo approaches to simulate the dynamics of many-body quantum systems classically. By systematically studying th…

quant-ph2023★ 12 cited

Learning ground states of gapped quantum Hamiltonians with Kernel Methods

Clemens Giuliani, Filippo Vicentini, Riccardo Rossi +1

Neural network approaches to approximate the ground state of quantum hamiltonians require the numerical solution of a highly nonlinear optimization problem. We introduce a statisti…

quant-ph2021★ 147 cited

NetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems

Filippo Vicentini, Damian Hofmann, Attila Szabó +8

We introduce version 3 of NetKet, the machine learning toolbox for many-body quantum physics. NetKet is built around neural-network quantum states and provides efficient algorithms…