Transcorrelated methods provide an efficient way of partially transferring the description of
electronic correlations from the ground-state wave function directly into the underlying …

This work proposes an iterative sparse-regularized regression method to recover governing
equations of nonlinear dynamical systems from noisy state measurements. The method is …

Real-and imaginary-time quantum state evolutions are crucial in physics and chemistry for
exploring quantum dynamics, preparing ground states, and computing thermodynamic …

Rock glaciers represent typical periglacial landscapes and are distributed widely in alpine
mountain environments. Rock glacier activity represents a critical indicator of water reserves …

Recent advances in the field of data-driven dynamics allow for the discovery of ODE systems
using state measurements. One approach, known as Sparse Identification of Nonlinear …

In recent years, identification of nonlinear dynamical systems from data has become
increasingly popular. Sparse regression approaches, such as sparse identification of …

Transcorrelated methods provide an efficient way of partially transferring the description of
electronic correlations from the ground state wavefunction directly into the underlying …

The L-curve is a popular heuristic to tune Tikhonov regularization in linear inverse problems.
This paper shows how it naturally arises when the problem is solved from a Bayesian …

Reinforcement learning is a growing field in AI with a lot of potential. Intelligent behavior is
learned automatically through trial and error in interaction with the environment. However …

Untethered small-scale robots can be potentially used in medical applications, such as
minimally invasive surgeries and targeted drug delivery. This article introduces a new …