Showing 661-680 of 817 projects
This repository provides hands-on examples and guidance for building, training, deploying and maintaining deep learning models in production.
This repository contains a PyTorch implementation of GIRAFFE, a generative model for representing 3D scenes as compositional neural feature fields.
Efficient Region-Aware Neural Radiance Fields for high-fidelity talking portrait synthesis
An all-in-one web UI for different audio-related neural networks, including text-to-speech, voice cloning, and generative music.
A Java library for building deep neural networks with GPU acceleration for machine learning and AI applications.
SincNet is a neural architecture for efficiently processing raw audio samples for speech and audio processing tasks.
Keras implementation of "One pixel attack for fooling deep neural networks" using differential evolution.
A Scala-based hardware accelerator for deep neural networks, part of Berkeley's AI hardware research.
An evolutionary algorithm library in Python for developers interested in AI and machine learning.
A library for keyword spotting on Arm Cortex-M microcontrollers using machine learning and the CMSIS-NN framework.
FeatherCNN is a high-performance inference engine for convolutional neural networks.
Code for a paper on feed-forward synthesis of textures and stylized images using neural networks.
A modular framework for building neural networks with Euclidean symmetry in Python.
A real-time emotion recognition library using computer vision and deep learning.
A JavaScript library that provides GPU-accelerated deep learning and neural network capabilities similar to PyTorch.
Multimodal AI toolkit for fast content understanding and generation across text, images, and video
A blazing-fast library for neuro-evolution and backpropagation in JavaScript, useful for AI and machine learning developers.
Sockeye is a PyTorch-based sequence-to-sequence framework for neural machine translation tasks.
Train, evaluate, optimize, and deploy computer vision models with OpenVINO, a toolkit for accelerating deep learning on edge devices.
An introductory series to Reinforcement Learning (RL) with comprehensive step-by-step tutorials.
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