Python Deep-neural-network Resources

DeepNLP-models-Pytorch Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ: NLP with Deep Learning) This is not for Pytorch be

pytorch-fcn PyTorch implementation of Fully Convolutional Networks. Requirements pytorch = 0.2.0 torchvision = 0.1.8 fcn = 6.1.5 Pillow scipy tqdm

This repository provides tutorial code for deep learning researchers to learn PyTorch. In the tutorial, most of the models were implemented with less

Table of Contents: Introduction to Torch's Tensor Library Computation Graphs and Automatic Differentiation Deep Learning Building Blocks: Affine maps,

Minimal tutorials for PyTorch adapted from Alec Radford's Theano tutorials. Tensor multiplication Linear Regression Logistic Regression Neural Network

C++ Implementation of PyTorch Tutorials for Everyone OS (Compiler)\LibTorch 1.9.0 macOS (clang 10.0, 11.0, 12.0) Linux (gcc 8, 9, 10, 11) Windows (msv

Deep Learning Models A collection of various deep learning architectures, models, and tips for TensorFlow and PyTorch in Jupyter Notebooks. Traditiona

Deep Learning Materials by Deep Learning Wizard Start Learning Now Please head to www.deeplearningwizard.com to start learning! It is mobile/tablet fr

Deep Learning (with PyTorch) This notebook repository now has a companion website, where all the course material can be found in video and textual for

D2L.ai: Interactive Deep Learning Book with Multi-Framework Code, Math, and Discussions Book website | STAT 157 Course at UC Berkeley | Latest version

Soft-Decision-Tree Soft-Decision-Tree is the pytorch implementation of Distilling a Neural Network Into a Soft Decision Tree, paper recently published

Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX, TensorFlow Lite, Keras, Caffe, Darknet, ncnn,

Hierarchical neural-net interpretations (ACD) 🧠 Produces hierarchical interpretations for a single prediction made by a pytorch neural network. Offic

Neural-Backed Decision Trees · Site · Paper · Blog · Video Alvin Wan, *Lisa Dunlap, *Daniel Ho, Jihan Yin, Scott Lee, Henry Jin, Suzanne Petryk, Sarah

MapExtrackt Convolutional Neural Networks Are Beautiful We all take our eyes for granted, we glance at an object for an instant and our brains can ide

Dream-Creator This project aims to simplify the process of creating a custom DeepDream model by using pretrained GoogleNet models and custom image dat

FlashTorch A Python visualization toolkit, built with PyTorch, for neural networks in PyTorch. Neural networks are often described as "black box". The

neural-dream This is a PyTorch implementation of DeepDream. The code is based on neural-style-pt. Here we DeepDream a photograph of the Golden Gate Br

Convolutional Neural Network Visualizations This repository contains a number of convolutional neural network visualization techniques implemented in

Class Activation Map methods implemented in Pytorch pip install grad-cam ⭐ Comprehensive collection of Pixel Attribution methods for Computer Vision.

Visualizing the Loss Landscape of Neural Nets This repository contains the PyTorch code for the paper Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer

Network Pruning That Matters: A Case Study on Retraining Variants (ICLR 2021)

Remixer - Pytorch Implementation of the Remixer Block from the Remixer paper, in Pytorch. It claims that substituting the feedforwards in transformers

Hierarchical Memory Matching Network for Video Object Segmentation Hongje Seong, Seoung Wug Oh, Joon-Young Lee, Seongwon Lee, Suhyeon Lee, Euntai Kim

Website | ArXiv | Get Start | Video PIRenderer The source code of the ICCV2021 paper "PIRenderer: Controllable Portrait Image Generation via Semantic

x-transformers A concise but fully-featured transformer, complete with a set of promising experimental features from various papers. Install $ pip ins

AlignShift NEW: Code for our new MICCAI'21 paper "Asymmetric 3D Context Fusion for Universal Lesion Detection" will also be pushed to this repository

Neural Distance Embeddings for Biological Sequences Official implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTo

TUT live age estimator Python implementation of a live deep learning based age/gender/smile/celebrity twin recognizer. All components use convolutiona

Website, Tutorials, and Docs    Uncertainty Toolbox A python toolbox for predictive uncertainty quantification, calibration, metrics, and visualizatio

DyStyle: Dynamic Neural Network for Multi-Attribute-Conditioned Style Editing Figure: Joint multi-attribute edits using DyStyle model. Great diversity

Hierarchical Memory Matching Network for Video Object Segmentation Hongje Seong, Seoung Wug Oh, Joon-Young Lee, Seongwon Lee, Suhyeon Lee, Euntai Kim

Muzic is a research project on AI music that empowers music understanding and generation with deep learning and artificial intelligence.

A Non-Autoregressive Transformer based TTS, supporting a family of SOTA transformers with supervised and unsupervised duration modelings. This project grows with the research community, aiming to achieve the ultimate TTS.

Lingvo is a framework for building neural networks in Tensorflow, particularly sequence models.

About subwAI subwAI - a project for training an AI to play the endless runner Subway Surfers using a supervised machine learning approach by imitation

A Closer Look at Structured Pruning for Neural Network Compression Code used to reproduce experiments in https://arxiv.org/abs/1810.04622. To prune, w

PyTorch implementation of [1611.06440 Pruning Convolutional Neural Networks for Resource Efficient Inference] This demonstrates pruning a VGG16 based

EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis This repo contains the official implementations of EigenDamage: Structured Prunin

model_based_energy_constrained_compression Code for paper "Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and

Example implementation of the L0 regularization method described at Learning Sparse Neural Networks through L0 regularization, Christos Louizos, Max W

Wiki and tutorials | Documentation | Getting Started | Algorithms | Design | FAQ Distiller is an open-source Python package for neural network compres

Code release for "Bayesian Compression for Deep Learning" In "Bayesian Compression for Deep Learning" we adopt a Bayesian view for the compression of

SpyTorch A tutorial on surrogate gradient learning in spiking neural networks Version: 0.4 This repository contains tutorial files to get you started

Intro PyTorch implementation of Learning to learn by gradient descent by gradient descent. Run python main.py TODO Initial implementation Toy data LST

OptNet: Differentiable Optimization as a Layer in Neural Networks This repository is by Brandon Amos and J. Zico Kolter and contains the PyTorch sourc

docTR by Mindee (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.

BMInf (Big Model Inference) is a low-resource inference package for large-scale pretrained language models (PLMs).

Container : Context Aggregation Network If you use this code for a paper please cite: @article{gao2021container, title={Container: Context Aggregati

FIDNet_SemanticKITTI Motivation Implementing complicated network modules with only one or two points improvement on hardware is tedious. So here we pr

DyStyle: Dynamic Neural Network for Multi-Attribute-Conditioned Style Editing

TensorFlow implementation of "A Simple Baseline for Bayesian Uncertainty in Deep Learning"

Bunch of optimizer implementations in PyTorch

Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot Compressive Imaging, ICCV2021 [PyTorch Code]

VeriNet The VeriNet toolkit is a state-of-the-art sound and complete symbolic interval propagation based toolkit for verification of neural networks.

LND ⚡ Routing High capacity, high availability, well connected, fast lightning node. We aim to become a top liquidity provider for the lightning netwo

RE2 This is a pytorch implementation of the ACL 2019 paper "Simple and Effective Text Matching with Richer Alignment Features". The original Tensorflo

GPU-accelerated PyTorch implementation of Zero-shot User Intent Detection via Capsule Neural Networks This repository implements a capsule model Inten

Splitter ⠀⠀ A PyTorch implementation of Splitter: Learning Node Representations that Capture Multiple Social Contexts (WWW 2019). Abstract Recent inte

WaveGlow A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis Quick Start: Install requirements: pip install

PyTorch Large-Scale Language Model A Large-Scale PyTorch Language Model trained on the 1-Billion Word (LM1B) / (GBW) dataset Latest Results 39.98 Perp

This is a fork of Fairseq(-py) with implementations of the following models: Pervasive Attention - 2D Convolutional Neural Networks for Sequence-to-Se

Structured Self-attentive sentence embeddings Implementation for the paper A Structured Self-Attentive Sentence Embedding, which was published in ICLR

Deepvoice3_pytorch PyTorch implementation of convolutional networks-based text-to-speech synthesis models: arXiv:1710.07654: Deep Voice 3: Scaling Tex

Non-Autoregressive Transformer Code release for Non-Autoregressive Neural Machine Translation by Jiatao Gu, James Bradbury, Caiming Xiong, Victor O.K.

Implementation of Deep-Forecast using PyTorch Deep Forecast: Deep Learning-based Spatio-Temporal Forecasting Adapted from original implementation Setu

SMASH: One-Shot Model Architecture Search through HyperNetworks An experimental technique for efficiently exploring neural architectures. This reposit

Retina Blood Vessels Segmentation This is an implementation of the research paper "Retina Blood Vessel Segmentation Using A U-Net Based Convolutional

face-vid2vid Usage Dataset Preparation cd datasets wget https://yt-dl.org/downloads/latest/youtube-dl -O youtube-dl chmod a+rx youtube-dl python load_

Tevatron Tevatron is a simple and efficient toolkit for training and running dense retrievers with deep language models. The toolkit has a modularized

TensorNets High level network definitions with pre-trained weights in TensorFlow (tested with 2.1.0 = TF = 1.4.0). Guiding principles Applicability.

Thingscoop: Utility for searching and filtering videos based on their content Description Thingscoop is a command-line utility for analyzing videos se

Shakespeare translations using TensorFlow This is an example of using the new Google's TensorFlow library on monolingual translation going from modern

Tensorforce: a TensorFlow library for applied reinforcement learning Introduction Tensorforce is an open-source deep reinforcement learning framework,

TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extens

Human-Level Control through Deep Reinforcement Learning Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning. This imp

DeepOSM Classify roads and features in satellite imagery, by training neural networks with OpenStreetMap (OSM) data. DeepOSM can: Download a chunk of

Pretty Tensor provides a high level builder API for TensorFlow. It provides thin wrappers on Tensors so that you can easily build multi-layer neural networks.

A best practice for tensorflow project template architecture.

SenseNet is a sensorimotor and touch simulator for deep reinforcement learning research

Seq2Seq in PyTorch This is a complete suite for training sequence-to-sequence models in PyTorch. It consists of several models and code to both train

Attention is all you need: A Pytorch Implementation This is a PyTorch implementation of the Transformer model in "Attention is All You Need" (Ashish V

pytorch-deeplab-resnet DeepLab resnet v2 model implementation in pytorch. The architecture of deepLab-ResNet has been replicated exactly as it is from

PyTorch-Style-Transfer This repo provides PyTorch Implementation of MSG-Net (ours) and Neural Style (Gatys et al. CVPR 2016), which has been included

Advantage async actor-critic Algorithms (A3C) in PyTorch @inproceedings{mnih2016asynchronous, title={Asynchronous methods for deep reinforcement lea

CycleGAN and pix2pix in PyTorch New: Please check out contrastive-unpaired-translation (CUT), our new unpaired image-to-image translation model that e

Deep-Leafsnap Convolutional Neural Networks have become largely popular in image tasks such as image classification recently largely due to to Krizhev

Deep Reinforcement Learning with pytorch & visdom Sample testings of trained agents (DQN on Breakout, A3C on Pong, DoubleDQN on CartPole, continuous A

Tree-Structured Long Short-Term Memory Networks This is a PyTorch implementation of Tree-LSTM as described in the paper Improved Semantic Representati

PyTorch implementation of Deformable Convolution !!!Warning: There is some issues in this implementation and this repo is not maintained any more, ple

SVHNClassifier-PyTorch A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks If

Attention Transfer PyTorch code for "Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Tran

PyTorch Tutorials This tutorial is no longer maintained. Please use the official version: https://pytorch.org/tutorials/advanced/neural_style_tutorial

FastNeuralStyle by Pytorch Fast Neural Style for Image Style Transform by Pytorch This is famous Fast Neural Style of Paper Perceptual Losses for Real

PytorchNeuralStyleTransfer Code to run Neural Style Transfer from our paper Image Style Transfer Using Convolutional Neural Networks. Also includes co

fast-neural-style 🌇 🚀 NOTICE: This codebase is no longer maintained, please use the codebase from pytorch examples repository available at pytorch/e

Intro PyTorch implementation of Learning to learn by gradient descent by gradient descent. Run python main.py TODO Initial implementation Toy data LST

DEPRECATION This repository is deprecated and is no longer maintaned. Please see a more recent implementation of RL for continuous control at jax-sac.

OptNet: Differentiable Optimization as a Layer in Neural Networks This repository is by Brandon Amos and J. Zico Kolter and contains the PyTorch sourc

Pytorch Squeeznet Pytorch implementation of Squeezenet model as described in https://arxiv.org/abs/1602.07360 on cifar-10 Data. The definition of Sque