Python Deep-neural-network Resources

Adaptive Segmentation Mask Attack This repository contains the implementation of the Adaptive Segmentation Mask Attack (ASMA), a targeted adversarial

This is a curated list of tutorials, projects, libraries, videos, papers, books and anything related to the incredible PyTorch. Feel free to make a pu

Draw like Bob Ross using the power of Neural Networks! (+ Pytorch) Learning Process Visualization Getting started Install dependecies Requires python3

The Malmo Collaborative AI Challenge - Team Pig Catcher Approach The challenge involves 2 agents who can either cooperate or defect. The optimal polic

sketchnet sketchnet - processing code generator can we teach a computer to draw pictures with code. We use Processing and java/jruby code paired with

Deep Learning Winter School, November 2107. Tel Aviv Deep Learning Bootcamp : http://deep-ml.com. About Tel-Aviv Deep Learning Bootcamp is an intensiv

Amazon Forest Computer Vision Satellite Image tagging code using PyTorch / Keras Here is a sample of images we had to work with Source: https://www.ka

Torchreid Torchreid is a library for deep-learning person re-identification, written in PyTorch. It features: multi-GPU training support both image- a

PyTorch Template Project PyTorch deep learning project made easy. PyTorch Template Project Requirements Features Folder Structure Usage Config file fo

Hasktorch Hasktorch is a library for tensors and neural networks in Haskell. It is an independent open source community project which leverages the co

Master Release Pytorch - Py + Nim A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen. Because Nim compiles to C+

UNet for segmenting salt deposits from seismic images with PyTorch. General We, tugstugi and xuyuan, have participated in the Kaggle competition TGS S

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

ocaml-torch provides some ocaml bindings for the PyTorch tensor library. This brings to OCaml NumPy-like tensor computations with GPU acceleration and tape-based automatic differentiation.

tch-rs Rust bindings for the C++ api of PyTorch. The goal of the tch crate is to provide some thin wrappers around the C++ PyTorch api (a.k.a. libtorc

All-in-one web-based development environment for machine learning Getting Started • Features & Screenshots • Support • Report a Bug • FAQ • Known Issu

Geometry-Consistent Neural Shape Representation with Implicit Displacement Fields [project page][paper][cite] Geometry-Consistent Neural Shape Represe

tymon An AI Assistant More Than a Toolkit The reason for creating framework tymon is simple. making AI more like an assistant, helping us to complete

HyperPose is a library for building high-performance custom pose estimation applications.

This repository contains a two-stage-tracker. The detections generated by YOLOv5, a family of object detection architectures and models pretrained on the COCO dataset, are passed to a Deep Sort algorithm which tracks the objects. It can track any object that your Yolov5 model was trained to detect.

RetinaFace is a deep learning based cutting-edge facial detector for Python coming with facial landmarks.

MONAI Label is a server-client system that facilitates interactive medical image annotation by using AI. It is an open-source and easy-to-install ecosystem that can run locally on a machine with one or two GPUs. Both server and client work on the same/different machine. However, initial support for multiple users is restricted. It shares the same principles with MONAI.

A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.

Densely Connected Time Delay Neural Network PyTorch implementation of Densely Connected Time Delay Neural Network (D-TDNN) in our paper "Densely Conne

Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes Introduction This is the unofficial code of Deep Dual-re

Logic Tensor Networks (LTN) Logic Tensor Network (LTN) is a neurosymbolic framework that supports querying, learning and reasoning with both rich data

2021-MICCAI-Progressively Normalized Self-Attention Network for Video Polyp Segmentation Authors: Ge-Peng Ji*, Yu-Cheng Chou*, Deng-Ping Fan, Geng Che

NU-Wave — Official PyTorch Implementation NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling Junhyeok Lee, Seungu Han @ MINDsLab Inc

Neural Logic Inductive Learning This is the implementation of the Neural Logic Inductive Learning model (NLIL) proposed in the ICLR 2020 paper: Learn

Depth-supervised NeRF: Fewer Views and Faster Training for Free Project | Paper | YouTube Pytorch implementation of our method for learning neural rad

Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets This is the official PyTorch implementation for the paper Rapid Neural A

**Codebase and data are uploaded in progress. ** VOLT(-py) is a vocabulary learning codebase that allows researchers and developers to automaticaly ge

Deep-Detail-Enhancement-for-Any-Garment Introduction This repository contains the implementation of Deep Detail Enhancment for Any Garment proposed in

SPARSEDNN **If you want to use this repo, please send me an email: [email protected], or raise a Github issue. ** Fast sparse deep learning on CPUs

Time Series Research with Torch 这个开源项目主要是对经典的时间序列预测算法论文进行复现，模型主要参考自GluonTS，框架主要参考自Informer。 建立原因 相较于mxnet和TF，Torch框架中的神经网络层需要提前指定输入维度： # 建立线性层 TensorF

Project page for the paper Semi-Supervised Raw-to-Raw Mapping 2021.

MNIST on the Web An attempt to predict MNIST handwritten digits from my PyTorch model from the browser (client-side) and not from the server, with the

WAGMA-SGD is a decentralized asynchronous SGD based on wait-avoiding group model averaging. The synchronization is relaxed by making the collectives externally-triggerable, namely, a collective can be initiated without requiring that all the processes enter it. It partially reduces the data within non-overlapping groups of process, improving the parallel scalability.

This software automatically sends you emails to notify you of the latest progress of your deep learning programs.

Official PyTorch implementation of the preprint paper "Stylized Neural Painting", accepted to CVPR 2021.

Spectral Tensor Train Parameterization of Deep Learning Layers This repository is the official implementation of our AISTATS 2021 paper titled "Spectr

The goal is to classify different birds species based on their songs/calls. Spectrograms have been extracted from the audio samples and used as features for classification.

imbalanced-DL: Deep Imbalanced Learning in Python Overview imbalanced-DL (imported as imbalanceddl) is a Python package designed to make deep imbalanc

This is my reading list for my PhD in AI, NLP, Deep Learning and more.

TensorRT examples (Jetson, Python/C++)(object detection)

Dual Self-Attention Network for Multivariate Time Series Forecasting 20.10.26 Update: Due to the difficulty of installation and code maintenance cause

GPRGNN This is the source code for our ICLR2021 paper: Adaptive Universal Generalized PageRank Graph Neural Network. Hidden state feature extraction i

Balancing Training for Multilingual Neural Machine Translation Implementation of the paper Balancing Training for Multilingual Neural Machine Translat

REval Table of Contents Introduction Overview Requirements Installation Probing Usage Citation License 🎓 Introduction REval is a simple framework for

Dpex——用户无感知分布式数据预处理组件 一、前言 随着GPU与CPU的算力差距越来越大以及模型训练时的预处理Pipeline变得越来越复杂，CPU部分的数据预处理已经逐渐成为了模型训练的瓶颈所在，这导致单机的GPU配置的提升并不能带来期望的线性加速。预处理性能瓶颈的本质在于每个GPU能够使用的C

Implicit Representations of Meaning in Neural Language Models Preliminaries Create and set up a conda environment as follows: conda create -n state-pr

Lightweight, efficient and stable implementations of deep reinforcement learning algorithms using PyTorch. 🔥

BrightNetworkUK-GCC-2021 This repo is related to Google Coding Challenge, given to Bright Network Internship Experience 2021. Language used here is py

Global Filter Networks for Image Classification Created by Yongming Rao, Wenliang Zhao, Zheng Zhu, Jiwen Lu, Jie Zhou This repository contains PyTorch

gym-anm is a framework for designing reinforcement learning (RL) environments that model Active Network Management (ANM) tasks in electricity distribution networks. It is built on top of the OpenAI Gym toolkit.

RoseTTAFold This package contains deep learning models and related scripts to run RoseTTAFold This repository is the official implementation of RoseTT

R-Drop: Regularized Dropout for Neural Networks R-drop is a simple yet very effective regularization method built upon dropout, by minimizing the bidi

DFM: A Performance Baseline for Deep Feature Matching Python (Pytorch) and Matlab (MatConvNet) implementations of our paper DFM: A Performance Baselin

CLCC: Contrastive Learning for Color Constancy (CVPR 2021) Yi-Chen Lo*, Chia-Che Chang*, Hsuan-Chao Chiu, Yu-Hao Huang, Chia-Ping Chen, Yu-Lin Chang,

ProGen - (wip) Implementation and replication of ProGen, Language Modeling for Protein Generation, in Pytorch and Jax (the weights will be made easily

FastPitchFormant - PyTorch Implementation PyTorch Implementation of FastPitchFormant: Source-filter based Decomposed Modeling for Speech Synthesis. Qu

AnalyticMesh Analytic Marching is an exact meshing solution from neural networks. Compared to standard methods, it completely avoids geometric and top

Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs In this work, we propose a framework HijackGAN, which enables non-linear latent space travers

Patch2Pix for Accurate Image Correspondence Estimation This repository contains the Pytorch implementation of our paper accepted at CVPR2021: Patch2Pi

Recurrent Fast Weight Programmers This is the official repository containing the code we used to produce the experimental results reported in the pape

PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing

Graph4NLP Graph4NLP is an easy-to-use library for R&D at the intersection of Deep Learning on Graphs and Natural Language Processing (i.e., DLG4NLP).

Graph Transformer - Pytorch Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2. This was recently used by bot

Fileshare 📨 Share files easily over your local network from the terminal! 📨 Installation # clone the repo $ git clone https://github.com/dopevog/fil

Embedding Transfer with Label Relaxation for Improved Metric Learning Official PyTorch implementation of CVPR 2021 paper Embedding Transfer with Label

Charformer - Pytorch Implementation of the GBST (gradient-based subword tokenization) module from the Charformer paper, in Pytorch. The paper proposes

A ready-to-use framework of latest models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, and etc.

Extensive tutorials for learning how to build deep learning models for causal inference using selection on observables in Tensorflow 2.

A data preprocessing package for time series data. Design for machine learning and deep learning.

Non-autoregressive Deep Learning-Based TTS Template This is a template for the Non-autoregressive TTS model. It contains Data Preprocessing Pipeline D

EdMIPS is an efficient algorithm to search the optimal mixed-precision neural network directly without proxy task on ImageNet given computation budgets. It can be applied to many popular network architectures, including ResNet, GoogLeNet, and Inception-V3.

CLIP (Contrastive Language–Image Pre-training) Experiments (Evaluation) Model Dataset Acc (%) ViT-B/32 (Paper) CIFAR100 65.1 ViT-B/32 (Our) CIFAR100 6

DeepCDR Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network This work has been accepted to ECCB2020 and was also published in the

Deep MVS gone wild Pytorch implementation of "Deep MVS gone wild" (Paper | website) This repository provides the code to reproduce the experiments of

SEDE SEDE (Stack Exchange Data Explorer) is new dataset for Text-to-SQL tasks with more than 12,000 SQL queries and their natural language description

DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation CVPR2021(oral) [arxiv] Requirements python3.7 pytorch==

SNN_Calibration Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021 Feature Comparison of SNN calibration: Features SNN Direct Tr

AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis | Project Page | Paper | PyTorch implementation for the paper "AD-NeRF: Audio

LibTraffic is a unified, flexible and comprehensive traffic prediction library, which provides researchers with a credibly experimental tool and a convenient development framework. Our library is implemented based on PyTorch, and includes all the necessary steps or components related to traffic prediction into a systematic pipeline.

Soft DTW Loss Function for PyTorch in CUDA This is a Pytorch Implementation of Soft-DTW: a Differentiable Loss Function for Time-Series which is batch

privalise Social Media Network Focuses On Data Security And Being Community Driven Web App The Main Idea: We`ve seen social media web apps that focuse

Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch

This repository is an implementation of Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis (SV2TTS) with a vocoder that works in real-time. Feel free to check my thesis if you're curious or if you're looking for info I haven't documented. Mostly I would recommend giving a quick look to the figures beyond the introduction.

Temporal network visualization This code is what I used to make the visualizations of SocioPatterns' primary school data here It requires the data of

PyTorch code to reproduce LyDROO algorithm [1], which is an online computation offloading algorithm to maximize the network data processing capability subject to the long-term data queue stability and average power constraints. It applies Lyapunov optimization to decouple the multi-stage stochastic MINLP into deterministic per-frame MINLP subproblems and solves each subproblem via DROO algorithm. It includes:

This project is one script (wpa_helper.py) written in python that will allow for the user to automate the proccess of setting up a new boot disk and configuring ssh and network settings for the pi

The inductive bias of a neural network is largely determined by the architecture and the training algorithm. To achieve good generalization, how to effectively train a neural network is of great importance. We propose a novel orthogonal over-parameterized training (OPT) framework that can provably minimize the hyperspherical energy which characterizes the diversity of neurons on a hypersphere. See our previous work -- MHE for an in-depth introduction.

DeepProbLog DeepProbLog is an extension of ProbLog that integrates Probabilistic Logic Programming with deep learning by introducing the neural predic

Neural G2P to portuguese language Grapheme-to-phoneme (G2P) conversion is the process of generating pronunciation for words based on their written for

Network-Shredder is a python based NIDS.

MolRep: A Deep Representation Learning Library for Molecular Property Prediction Summary MolRep is a Python package for fairly measuring algorithmic p

WaveGrad2 - PyTorch Implementation PyTorch Implementation of Google Brain's WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis. Status (202

CausaLM: Causal Model Explanation Through Counterfactual Language Models Authors: Amir Feder, Nadav Oved, Uri Shalit, Roi Reichart Abstract: Understan

OOD-detection-using-OECC This repository contains the essential code for the paper Outlier Exposure with Confidence Control for Out-of-Distribution De

NonCuboidRoom Paper Learning to Reconstruct 3D Non-Cuboid Room Layout from a Single RGB Image Cheng Yang*, Jia Zheng*, Xili Dai, Rui Tang, Yi Ma, Xiao