Hong-Ye Hu's Projects
A pedagogical implementation of Autograd
Autoregressive model for solving statistical mechanics problems
Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
Simulating Rydberg atom dynamics with Tensor Networks
Toolkit for fermonic simulations and fermionic quantum computation in Julia.
Download images from flickr (eg: dogs and cats) and use them for machine learning
A PyTorch implementation of a Generative Flow Network (GFlowNet) proposed by Bengio et al. (2021)
GflowNets, MCMC, Metropolis-Hasting, Gibbs sampling, Metropolis-adjusted Langevin, Inverse Transform Sampling, Acceptance-Rejection Method and Important Sampling
A blog introducing the idea of classical shadow tomography, and Hamiltonian-driven shadow tomography of quantum states(https://arxiv.org/pdf/2102.10132.pdf)
An **unofficial** pytorch implementation of using generative models to do quantum state tomography with POVM measurements.
Mathematica Packages for Physicists
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Neural Network Decoders for Quantum Error Correcting Codes
Pytorch source code for arXiv paper Neural Network Renormalization Group, a generative model using variational renormalization group and normalizing flow.
The Official PyTorch Implementation of "NVAE: A Deep Hierarchical Variational Autoencoder" (NeurIPS 2020 spotlight paper)
An intuitive programming package for simulating and analyzing Clifford circuits, quantum measurement, and stabilizer states with applications to many-body localization, classical shadows, quantum chemistry and error correction code.
This is the documents and tutorials of PyClifford simulator
Clifford circuits, graph states, and other quantum Stabilizer formalism tools.
Quantum Optimal Control with Direct Collocation
QuTiP: Quantum Toolbox in Python
This is a QuTip extension including several functions and Hamiltonians
This is project page for the paper "RG-Flow: a hierarchical and explainable flow model based on renormalization group and sparse prior". Paper link: https://arxiv.org/abs/2010.00029
This is a toy model of RNVP flow model, where the neural network is implemented as a fully connected resnet.
Official implementation of spectrum bifurcation renormalization group(SBRG), which is suitable for quantum simulation on strong disordered systems for 1D and 2D. Paper: arXiv:2008.02285[https://arxiv.org/abs/2008.02285], Phys. Rev. B 93, 104205 (2016)[https://arxiv.org/abs/1508.03635]
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