There are 1 repository under pyro topic.
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
Telegram Group Manager Bot Written In Python Using Pyrogram.
A framework for hydrodynamics explorations and prototyping
ASR with PyTorch
Invariant representation learning from imaging and spectral data
𝒫robabilistic modeling of RNA velocity ⬱
[BMM 24-25] "Just Relax It": Implementation of different relaxation methods
Colab notebooks exploring different Machine Learning topics.
Deep Probabilistic Programming Examples in Pytorch using pyro
Deep Learning Regression and Classification Library built on top of PyTorch and Pyro
Generate dynamic structural causal models from biological knowledge graphs encoded in the Biological Expression Language (BEL)
A Telegram Bot That Can Find Lyrics Of Song
ARIMA time series implementation in PyTorch with optional support for Bayesian priors.
Implementation of a Mixture Density Network in the deep probabilistic programming language Pyro.
bvas: bayesian viral allele selection
Bayesian deep learning experiments
Yocto BSP layer for the nvidia jetson tx2 boards.
A tutorial on probabilistic programming with deep learning, stochastic variational inference, MCMC and other useful tricks. Based in pytorch/pyro.
An experimental Python package for learning Bayesian Neural Network.
Tutorials for the 2022 IAIFI Summer School, covering (deep) probabilistic programming with Jax and NumPyro.
Proof-of-principle application of Gaussian process modeling to gamma-ray analyses. Code repository associated with the paper https://arxiv.org/abs/2010.10450.
ASLS' CueOS designed for Arm® Cortex-M4 Microcontrollers provides built-in show control features such as multi-protocol Cue triggering, diverse control outputs and show programmation through web interface.
Pyro code for reproducing examples from John Winns MBML book.
Meet Uber's Pyro - popular framework for probabilistic programming. Learn how to introduce regularization and prior assumptions into a model, at first for a simple use case of Bayesian Linear Regression and later in an introduction to deep generative models with Pyro.
A powerful Pagination Help Library For Pyrogram with inbuilt features 📖
Deep probabilistic modeling with Pyro. This repository includes various probabilistic models developed based on Pyro, a deep universal probabilistic programming framework backed by PyTorch.