Stars
A Python library for amortized Bayesian workflows using generative neural networks.
Code repository for Continuous Conditional Diffusion Model (CCDM)
Implementation of Perceiver AR, Deepmind's new long-context attention network based on Perceiver architecture, in Pytorch
Chat with GitHub Copilot in Neovim
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
🦀 Small exercises to get you used to reading and writing Rust code!
Notebook to go along with a lecture for the MIT course 8.16: Data Science in Physics on neural simulation-based inference.
Lightweight coding agent that runs in your terminal
PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡
A simple, fast and user-friendly alternative to 'find'
Live training loss plot in Jupyter Notebook for Keras, PyTorch and others
Hydra is a framework for elegantly configuring complex applications
Iconic font aggregator, collection, & patcher. 3,600+ icons, 50+ patched fonts: Hack, Source Code Pro, more. Glyph collections: Font Awesome, Material Design Icons, Octicons, & more
TorchCFM: a Conditional Flow Matching library
JupyterLab desktop application, based on Electron.
A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)
A PyTorch library for implementing flow matching algorithms, featuring continuous and discrete flow matching implementations. It includes practical examples for both text and image modalities.
Free-form flows are a generative model training a pair of neural networks via maximum likelihood
Rust for data analysis encyclopedia (WIP).
A privacy-first, open-source platform for knowledge management and collaboration. Download link: http://github.com/logseq/logseq/releases. roadmap: https://discuss.logseq.com/t/logseq-product-roadm…
The fastest and simplest library for SQLite3 in Node.js.
A framework for fast simulation of a generic collider experiment
Open-source framework for uncertainty and deep learning models in PyTorch 🌱
High-quality implementations of standard and SOTA methods on a variety of tasks.
A technical report on convolution arithmetic in the context of deep learning