An electronic structure package based on either plane wave basis or numerical atomic orbitals.

Roundtrip latex to orgmode converter

Tools to download and cleanup Common Crawl data

The TinyLlama project is an open endeavor to pretrain a 1.1B Llama model on 3 trillion tokens.

Ongoing research training transformer models at scale

The official repo of Qwen (通义千问) chat & pretrained large language model proposed by Alibaba Cloud.

Implementation of papers in 101 lines of code.

Deep neural networks for density functional theory Hamiltonian.

A header-only C++ library for sketching in randomized linear algebra

AlgoPy is a Research Prototype for Algorithmic Differentation in Python

Manopt, a Matlab toolbox for optimization on manifolds

Kolmogorov Arnold Networks

Auriga is a minimalist LaTeX beamer presentation theme 📽

A minimalist Beamer theme with a watermark in the background

Fast implementation of the multi-dimensional fractional Fourier transform in Python

Julia implementation of the Non-equidistant Fast Fourier Transform (NFFT)

Differentiable Fluid Dynamics Package

Code for Neural Spline Flows paper

Normalizing flows in PyTorch

Riemannian Convex Potential Maps

JAX exponential map normalising flows on sphere

This is a Pytorch implementation of [normalizing flows on tori and spheres, ICML 2020]

LaTeX style for NUS Qualifying Examination.

A benchmark for Goertzel algorithm and `scipy.fftpack.fft` (with custom implementation of Goertzel algorithm in short-time version) **for evaluating a few DFT terms**

Automatic Functional Differentiation in JAX

Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations

Source code related to the article "Deep splitting method for parabolic PDEs" by Christian Beck, Sebastian Becker, Patrick Cheridito, Arnulf Jentzen, and Ariel Neufeld

A collection of python scripts that deal with VASP outpts, e.g. WAVECAR, POTCAR etc.

A JAX based package designed for efficient second order operators (e.g., laplacian) computation.

Efficient and Accurate Neural-Network Ansatz for Quantum Monte Carlo