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aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
This repository contains the source code for the paper First Order Motion Model for Image Animation
Silero Models: pre-trained text-to-speech models made embarrassingly simple
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
Probabilistic reasoning and statistical analysis in TensorFlow
[CVPR 2024] 4D Gaussian Splatting for Real-Time Dynamic Scene Rendering
Bayesian optimization in PyTorch
[SIGGRAPH Asia 2022] VToonify: Controllable High-Resolution Portrait Video Style Transfer
Book_7_《机器学习》 | 鸢尾花书：从加减乘除到机器学习；欢迎批评指正
[SIGGRAPH Asia 2023] Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translation
Bayesian optimisation & Reinforcement Learning library developed by Huawei Noah's Ark Lab
We unified the interfaces of instruction-tuning data (e.g., CoT data), multiple LLMs and parameter-efficient methods (e.g., lora, p-tuning) together for easy use. We welcome open-source enthusiasts to initiate any meaningful PR on this repo and integrate as many LLM related technologies as possible. 我们打造了方便研究人员上手和使用大模型等微调平台，我们欢迎开源爱好者发起任何有意义的pr！
Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop
A python tutorial on bayesian modeling techniques (PyMC3)
Code for "GVHMR: World-Grounded Human Motion Recovery via Gravity-View Coordinates", Siggraph Asia 2024, TPAMI 2026
PyMC educational resources
Text and code for the second edition of Think Bayes, by Allen Downey.
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Notebooks about Bayesian methods for machine learning
A Modular Framework for 3D Gaussian Splatting and Beyond
Generate images from texts. In Russian
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
Python package for Bayesian Machine Learning with scikit-learn API