Neural Networks
Showing 36 of 159 projects
A JAX-based neural network library that provides a simple, object-oriented programming model for building and training models.
A curated list of deep learning image classification papers and their code implementations since 2014.
A curated list of scientific articles, theses, and reports on deep learning applied to music information retrieval and generation.
A JavaScript library for real-time hand detection and pose classification directly in the browser using TensorFlow.js.
A JAX library for neural networks and scientific computing with PyTorch-like syntax and full ecosystem compatibility.
An interactive online learning platform for computer vision with a comprehensive Chinese ebook, code, and community.
Convert Caffe deep learning models to TensorFlow format for deployment and inference.
A deep learning framework for research, development, and production with flexible Python API and C++ core.
A TensorFlow library for Learning-to-Rank (LTR) techniques, providing loss functions, metrics, and models for ranking tasks.
A comprehensive collection of machine learning algorithms and mathematical utilities implemented in JavaScript for browser and Node.js.
A benchmarking suite comparing the performance of public convolutional neural network implementations across multiple deep learning frameworks.
Deep neural network to extract structured information from invoice documents with a customizable UI and training tools.
A JAX-native library implementing Monte Carlo tree search algorithms like AlphaZero and MuZero for reinforcement learning research.
A collection of beginner-friendly TensorFlow tutorials using Jupyter Notebook, covering deep learning fundamentals and practical applications.
TensorFlow implementation of Deep Q-Networks (DQN) for human-level control in reinforcement learning environments.
A Python library for graph deep learning built on Keras and TensorFlow 2, providing flexible tools for graph neural networks.
A modular toolkit for machine learning, natural language processing, and text generation with TensorFlow and PyTorch versions.
A high-level neural network API for specifying and analyzing infinite-width neural networks as Gaussian Processes in Python.
A machine learning package implementing message passing neural networks for predicting molecular and reaction properties.
A flow-based generative network for fast, high-quality speech synthesis from mel-spectrograms.
A minimal, well-tested library for training and using feedforward artificial neural networks in ANSI C.
A high-performance C++ image processing and machine learning library optimized with SIMD instructions across multiple CPU architectures.
A deep learning system for accurate protein structure and interaction prediction using a three-track neural network.
A curated list of awesome libraries, data sources, tutorials, and resources for machine learning using the Ruby programming language.
A curated list of libraries, tutorials, and resources for implementing machine learning in the Ruby programming language.
PyGAD is a Python library for building genetic algorithms and optimizing machine learning models with Keras and PyTorch support.
A simple wrapper that combines Keras and Hyperopt for convenient hyperparameter optimization in deep learning models.
A curated list of awesome libraries, projects, tutorials, and resources for the JAX machine learning ecosystem.
A Python library for constructing differentiable convex optimization layers in PyTorch, JAX, and MLX using CVXPY.
An end-to-end Python pipeline for semantic segmentation of aerial and satellite imagery to extract features like buildings and roads.
A framework for running deep neural network models directly in web browsers using ONNX format with WebGPU, WebGL, and WebAssembly backends.
A JAX-based library providing numerical differential equation solvers for ODEs, SDEs, and CDEs with autodifferentiation and GPU support.
A deep learning library for Rust featuring shape-checked tensors and neural networks with compile-time safety.
A deep learning library in Rust featuring shape-checked tensors and neural networks with compile-time safety.
A curated list of resources for adversarial machine learning, covering attacks, defenses, and research.
A JAX research toolkit for building, editing, and visualizing neural networks as legible, functional pytree data structures.
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