A Collection of Variational Autoencoders (VAE) in PyTorch.

Gradient-descent quantum process tomography by learning Kraus operators

Pytorch🍊🍉 is delicious, just eat it! 😋😋

depyf is a tool to help you understand and adapt to PyTorch compiler torch.compile.

Riemannian optimization for quantum technologies

📚 天涯帖子备份

Toolset for control, calibration and characterization of physical systems

Model-Free Quantum Control with Reinforcement Learning.

Model-Free Quantum Control with Reinforcement Learning.

计算机自学指南

[ICLR 2023] One Transformer Can Understand Both 2D & 3D Molecular Data (official implementation)

emoji list; emoji表情列表

Uniform Manifold Approximation and Projection

PyTorch入门教程，在线阅读地址：https://datawhalechina.github.io/thorough-pytorch/

Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

QuTiP: Quantum Toolbox in Python

PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

The QuTiP quantum information processing package

Robotics Toolbox for MATLAB