mashiyuan67

neural-network-for-nonlocality-in-networks

Code for the work in: https://www.nature.com/articles/s41534-020-00305-x Basically a generative neural network to tackle the classical causal inference problem encountered in quantum network nonlocality.

Single-Photon-Detection-Neural-Networks

Physics-aware stochastic training for single-photon-detection neural networks (SPDNNs)

wgan-gp

A pytorch implementation of Paper "Improved Training of Wasserstein GANs"

improved_wgan_training

Code for reproducing experiments in "Improved Training of Wasserstein GANs"

RWKV-LM

RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.

Wasserstein-Generative-Adversarial-Network

In this Machine Learning Exam I created two types of Generative Adversarial Networks (GANs) with different loss functions. The aim of the two networks is to train the generator network to generate samples from a given probability distribution in a way that the discriminator cannot distinguish it from real samples. In this example I worked with data from a 2D Ising Model which is one of the most successful and broadly applicable models in statistical physics.

qovae

QuDDPM_reproduce_and_extend

Code to reproduce paper regarding quantum diffusion model and extend: Zhang, Bingzhi, et al. "Generative quantum machine learning via denoising diffusion probabilistic models." arXiv preprint arXiv:2310.05866 (2023).

stable-diffusion

A latent text-to-image diffusion model

Correlated-VAEs

Code for my ICML 2019 paper "Correlated Variational Auto-Encoders"

VAE

Implementation of VAE and CVAE using Pytorch on MNIST dataset

dynamiqs

High-performance quantum systems simulation with JAX (GPU-accelerated & differentiable solvers).

set_transformer

Pytorch implementation of set transformer

deepoptics

NC

NCAlgebra - Non Commutative Algebra Package for Mathematica

GaussianSSF.jl

Quantum split-step Fourier simulations for nonlinear Gaussian-state pulse propagation

Quantum-Gaussian-Information-Toolbox

QuGIT is a numerical toolbox in Python for simulation of gaussian quantum states and their time evolution through unconditional and conditional dynamics

pytorch-image-models

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

DenseNet

This repository contains a PyTorch implementation of the paper Densely Connected Convolutional Networks trained on the MNIST dataset. The code is based on this excellent PyTorch example for training DenseNet.(https://github.com/pytorch/vision/blob/master/torchvision/models/densenet.py)

RepLKNet

Official MegEngine implementation of RepLKNet

MLP-Mixer-CIFAR10

Implements MLP-Mixer (https://arxiv.org/abs/2105.01601) with the CIFAR-10 dataset.

adversarial-autoencoder

Chainer implementation of adversarial autoencoder (AAE)

binary-stochastic-neurons

Binary Stochastic Neurons in PyTorch

BinaryNet

Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

Adversial_AutoEncoder

Adversial AutoEncoder in PyTorch

MLExp

binarygan

Code for "Training Generative Adversarial Networks with Binary Neurons by End-to-end Backpropagation"

Pytorch-autoencoder-mlp

MLP for MNIST Classification(Autoencoder_Pretrain)

GBS_classicality

diffusion

Denoising Diffusion Probabilistic Models