Popular GitHub Repositories for Langevin Mc

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

Code for "A-NICE-MC: Adversarial Training for MCMC"

AI Agent Simulation generates Minecraft Settlements

Ying Nian Wu's UCLA Statistical Machine Learning Tutorial on generative modeling.

A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesian Deep Learning, by providing an overview of key papers. More details: "A Primer on Bayesian Neural Networks: Review and Debates"

[NeurIPS 2021] SNIPS: Solving Noisy Inverse Problems Stochastically

a python implementation of MC-CNN

? Energy-Based Modeling library for PyTorch, offering tools for sampling, inference, and learning in complex distributions.

Implementation of the model: "(MC-ViT)" from the paper: "Memory Consolidation Enables Long-Context Video Understanding"

Variational Inference for Langevin Equations

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).

An experimental Python package for learning Bayesian Neural Network.

MC-DARTS : Model Size Constrained Differentiable Architecture Search

Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches

Computational & Deep Learning Frameworks Benchmark

Bayesian Structured Time Series Analysis with Parallel Tempering for Stock Market Prediction

An implementation of the MC-AIXI-CTW paper

Code for "Sufficient conditions for offline reactivation in recurrent neural networks" (ICLR 2024)

Gratis, rápido, portátil y optimizado, ¿Algo más?

一个可能让你眼前一亮的MC Fabric模组，集成了LLM（大语言模型）聊天功能，支持多种AI服务和自定义功能。