Neural Networks
Showing 36 of 428 projects
A deep learning library for 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.
A self-contained machine learning and natural language processing library written in pure Go with a dynamic computational graph.
A deep learning model for protein sequence design that generates amino acid sequences for given protein backbones.
A collection of interactive machine learning experiments with Jupyter notebooks for training and browser demos for visualization.
A curated collection of high-quality deep learning resources, including courses, books, papers, libraries, and datasets.
A library for creating TensorFlow models that handle structured data with dynamic computation graphs using dynamic batching.
An abstraction layer over MetalPerformanceShaders for crafting and running fast neural networks on iOS using TensorFlow models.
Implementations of memory-augmented neural networks for language modeling, dialogue systems, and question answering tasks.
An easy-to-use, state-of-the-art named-entity recognition (NER) tool based on neural networks.
A neural network library for Elixir built on Nx, providing functional, model creation, and training APIs for deep learning.
A unified framework for implementing and training deep learning models on tabular data using PyTorch and PyTorch Lightning.
A language for distributed deep learning that simplifies model parallelism by specifying tensor computations across hardware meshes.
A deprecated repository for community-contributed Keras extensions like layers, activations, and loss functions.
A high-level Deep Learning API for JVM and Android developers, written in Kotlin and inspired by Keras.
Elephas is a Keras extension for distributed deep learning on Apache Spark, enabling data-parallel training at scale.
An efficient neural network for semantic segmentation of large-scale 3D point clouds using random sampling.
A JAX-based library providing reinforcement learning building blocks for implementing agents, supporting both on-policy and off-policy learning.
A deep learning framework for Julia with GPU support and automatic differentiation using dynamic computational graphs.
A technique using Fourier feature mappings to enable neural networks to learn high-frequency functions in low-dimensional domains.
A Pythonic deep learning framework built on NumPy with optional CUDA acceleration.
A deep learning technique for finding semantically-meaningful dense correspondences between images to enable visual attribute transfer.
A modular neural network package for Torch providing building blocks for creating and training deep learning models.
A dedicated OCaml system for scientific and engineering computing, providing n-dimensional arrays, linear algebra, algorithmic differentiation, and neural networks.
A visual debugger for TensorFlow with breakpoints and real-time data visualization during neural network training.
Train neural networks with OpenStreetMap data and satellite imagery to classify roads and map features.
A discontinued Python neural network framework designed for fast, flexible experimentation with CPU and GPU backends.
A minimalist neural network library optimized for sparse data and single-machine environments.
A deep learning framework for Julia inspired by Caffe, featuring modular architecture and multiple backends.
A Clojure library for neural networks, regression, and feature learning with GPU acceleration support.
A general-purpose machine learning library for Rust, focusing on speed and ease of use with minimal dependencies.
A library for building high-performance custom human pose estimation applications with real-time inference and flexible model development.
A Java deep learning framework implementing neural networks with GPU acceleration via OpenCL and Aparapi.
A high-level builder API for TensorFlow that enables fluent, chainable neural network construction.
A deep learning JavaScript library built from scratch with PyTorch-like syntax and GPU acceleration via GPU.js.
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