Popular GitHub Repositories for Hamiltonian

Bayesian inference with probabilistic programming.

Machine learning algorithms for many-body quantum systems

Code for our paper "Hamiltonian Neural Networks"

Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python

AI research environment for the game of Snake ? .

A library for building differential equations arising from physical problems for physics-informed and scientific machine learning (SciML)

Code for our RSS'21 paper: "Hamiltonian-based Neural ODE Networks on the SE(3) Manifold For Dynamics Learning and Control"

A blog introducing the idea of classical shadow tomography, and Hamiltonian-driven shadow tomography of quantum states(https://arxiv.org/pdf/2102.10132.pdf)

Using deep reinforcement learning to play Snake game. The used algorithm is PPO for discrete! It has the brilliant performance in the field of discrete action space just like in continuous action space. You just need half an hour to train the snake and then it can be as smart as you.|使用深度强化学习玩蛇游戏。 使用的算法是离散的 PPO！ 它在离散动作空间领域有着与连续动作空间一样的出色表现。

Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods

The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural Networks (DNNs), Neural ODEs, and Symplectic Neural Networks (SympNets) used with state-of-the-art sampling schemes like Hamiltonian Monte Carlo (HMC) and the No-U-Turn-Sampler (NUTS).

Official code for HH-VAEM

An experimental Python package for learning Bayesian Neural Network.

Hamiltonian Annealed Importance Sampling (HAIS) in tensorflow

A parallelized brute-force program for finding and plotting all shortest paths that touch every square in an n by n grid

A few proofs and examples related to ML/Prob and Optimisation

Bayesian Neural Networks implemented in Julia using variational inference and Hamiltonian Monte Carlo sampling.

? SNAKE AI - Had, který vždy vyhraje! ???

Python package for constructing molecular rovibrational kinetic and potential energy operators using Taylor-mode automatic differentiation