Stars
This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Descent"
Implementation for the paper "Learning Non-linear Wavelet Transformation via Normalizing Flow"(arXiv:2101.11306)
Access and analyze historical weather and climate data with Python.
Physics-Informed Neural networks for Advanced modeling
FlowBasis: Variational solutions of perturbed quantum harmonic oscillator problems via augmented basis sets.
ALPES: Stochastic active learning of potential energy surfaces.
Tutorial on computational astrophysics
(yet another) static site generator. Simple, customisable, fast, maths with KaTeX, code evaluation, optional pre-rendering, in Julia.
The repository contains Jupyter notebooks for hands-on tutorials organized within the Summer School: Machine Learning for Quantum Physics and Chemistry (24th August - 3rd September 2021, Warsaw).
Richmol is for variational simulations of molecular nuclear motion dynamics in fields
Numerical integration in arbitrary dimensions on the GPU using PyTorch / TF / JAX
TensorFlow, PyTorch and Numpy layers for generating Orthogonal Polynomials
gcarleo / netket
Forked from netket/netketMachine learning algorithms for many-body quantum systems
Stuff for educational purposes, mainly machine learning, Python and statistics
Basic Qiskit Tutorials prepared for the RWTH block course on quantum computing
Deep learning quantum Monte Carlo for electrons in real space
Implementation of Spectral Inference Networks, ICLR 2019
Code and website for DAL (Discriminative Active Learning) - a new active learning algorithm for neural networks in the batch setting. For the blog:
Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations