Open source neural network chess engine with GPU acceleration and broad hardware support.
The Compute Library is a set of computer vision and machine learning functions optimised for both Arm CPUs and GPUs using SIMD technologies.
Distributed LLM inference. Connect home devices into a powerful cluster to accelerate LLM inference. More devices means faster inference.
Tiny, no-nonsense, self-contained, Tensorflow and ONNX inference
AI Roadmap:机器学习(Machine Learning)、深度学习(Deep Learning)、对抗神经网络(GAN),图神经网络(GNN),NLP,大数据相关的发展路书(roadmap), 并附海量源码(python,pytorch)带大家消化基本知识点,突破面试,完成从新手到合格工程师的跨越,其中深度学习相关论文附有tensorflow caffe官方源码,应用部分含推荐算法和知识图谱
Everything we actually know about the Apple Neural Engine (ANE)
Message Passing Neural Networks for Molecule Property Prediction
High-efficiency floating-point neural network inference operators for mobile, server, and Web
A curated collection of papers, benchmarks, surveys, and tools for model quantization, covering low-bit networks, LLMs, multimodal and generative models, vector and lattice quantization, and efficient deployment.
A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine
The collection of pre-trained, state-of-the-art AI models for ailia SDK
C++ image processing and machine learning library with using of SIMD: SSE, AVX, AVX-512, AMX for x86/x64, NEON, SVE for ARM, HVX for Hexagon
Bayesian inference with probabilistic programming.
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
Machine learning on FPGAs using HLS
SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.
Deep and online learning with spiking neural networks in Python
Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)
Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)
The Fastest DNN Running Framework on Web Browser
Training PyTorch models with differential privacy
Implementation of "BitNet: Scaling 1-bit Transformers for Large Language Models" in pytorch
Transform geospatial relations into graphs for Graph Neural Networks and spatial network analysis
A lightweight library for PyTorch training tools and utilities
Simulation of spiking neural networks (SNNs) using PyTorch.
Nx-powered Neural Networks
GoMLX: An Accelerated Machine Learning Framework For Go
A PyTorch library and evaluation platform for end-to-end compression research
:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps
High-quality implementations of standard and SOTA methods on a variety of tasks.
Brevitas: neural network quantization in PyTorch
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
List of papers studying machine learning through the lens of category theory
Multi-class confusion matrix library in Python
A group of notebooks and other files which can help you learn AI from scratch.
A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends
Build, train, optimize, and run computer vision models locally, from raw images to live inference. Open source, optimized for Intel XPU (CPU-only and CUDA also supported).
Owl - OCaml Scientific Computing @ https://ocaml.xyz
Arm NN ML Software.
Brian is a free, open source simulator for spiking neural networks.
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
Protein Graph Library
Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE.
The nnsight package enables interpreting and manipulating the internals of deep learned models.
OCR engine for all the languages
Dataflow compiler for QNN inference on FPGAs
Active learning for systematic reviews
[IEEE T-KDE 2026] Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
Training neural models with structured signals.
Machine Learning Open Source University
JAX in JavaScript – ML library for the web, running on WebGPU & Wasm
SchNetPack - Deep Neural Networks for Atomistic Systems
Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
Free and fully open-source L2 ADAS stack powered by End-to-End AI technology
Enhance Images with Javascript and AI. Increase resolution, retouch, denoise, and more. Open Source, Browser & Node Compatible, MIT License.
This repo is the homebase of a community driven course on Computer Vision with Neural Networks. Feel free to join us on the Hugging Face discord: hf.co/join/discord
A comprehensive book on neural networks and large language models in NLP
A pytorch library for graph and hypergraph computation.
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
A high performance Vector Database leveraging parallel graph computing