12799 Repositories
Python learning-models-and-generalization Libraries
A boilerplate Flask API for a Fullstack Project with some additional packages and configuration prebuilt. ⚙
Flask Boilerplate to quickly get started with production grade flask application with some additional packages and configuration prebuilt.
Pytorch implementation of the paper "Optimization as a Model for Few-Shot Learning"
Optimization as a Model for Few-Shot Learning This repo provides a Pytorch implementation for the Optimization as a Model for Few-Shot Learning paper.
meProp: Sparsified Back Propagation for Accelerated Deep Learning
meProp The codes were used for the paper meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting (ICML 2017) [pdf]
Continuum Learning with GEM: Gradient Episodic Memory
Gradient Episodic Memory for Continual Learning Source code for the paper: @inproceedings{GradientEpisodicMemory, title={Gradient Episodic Memory
Image Deblurring using Generative Adversarial Networks
DeblurGAN arXiv Paper Version Pytorch implementation of the paper DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks. Our netwo
StarGAN - Official PyTorch Implementation
StarGAN - Official PyTorch Implementation ***** New: StarGAN v2 is available at https://github.com/clovaai/stargan-v2 ***** This repository provides t
PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules
Dynamic Routing Between Capsules - PyTorch implementation PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules from Sara Sabour,
CondenseNet: Light weighted CNN for mobile devices
CondenseNets This repository contains the code (in PyTorch) for "CondenseNet: An Efficient DenseNet using Learned Group Convolutions" paper by Gao Hua
Image restoration with neural networks but without learning.
Warning! The optimization may not converge on some GPUs. We've personally experienced issues on Tesla V100 and P40 GPUs. When running the code, make s
Deep Learning Head Pose Estimation using PyTorch.
Hopenet is an accurate and easy to use head pose estimation network. Models have been trained on the 300W-LP dataset and have been tested on real data with good qualitative performance.
Random Erasing Data Augmentation. Experiments on CIFAR10, CIFAR100 and Fashion-MNIST
Random Erasing Data Augmentation =============================================================== black white random This code has the source code for
Synthesizing and manipulating 2048x1024 images with conditional GANs
pix2pixHD Project | Youtube | Paper Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic image-to-image translatio
SmoothGrad implementation in PyTorch
SmoothGrad implementation in PyTorch PyTorch implementation of SmoothGrad: removing noise by adding noise. Vanilla Gradients SmoothGrad Guided backpro
PyTorch implementation of the YOLO (You Only Look Once) v2
PyTorch implementation of the YOLO (You Only Look Once) v2 The YOLOv2 is one of the most popular one-stage object detector. This project adopts PyTorc
PyTorch Implementation of Realtime Multi-Person Pose Estimation project.
PyTorch Realtime Multi-Person Pose Estimation This is a pytorch version of Realtime_Multi-Person_Pose_Estimation, origin code is here Realtime_Multi-P
Pytorch Implementation of Interaction Networks for Learning about Objects, Relations and Physics
Interaction-Network-Pytorch Pytorch Implementraion of Interaction Networks for Learning about Objects, Relations and Physics. Interaction Network is a
PyTorch implementation of 1712.06087 "Zero-Shot" Super-Resolution using Deep Internal Learning
Unofficial PyTorch implementation of "Zero-Shot" Super-Resolution using Deep Internal Learning Unofficial Implementation of 1712.06087 "Zero-Shot" Sup
Image reconstruction done with untrained neural networks.
PyTorch Deep Image Prior An implementation of image reconstruction methods from Deep Image Prior (Ulyanov et al., 2017) in PyTorch. The point of the p
Train an RL agent to execute natural language instructions in a 3D Environment (PyTorch)
Gated-Attention Architectures for Task-Oriented Language Grounding This is a PyTorch implementation of the AAAI-18 paper: Gated-Attention Architecture
Canonical Appearance Transformations
CAT-Net: Learning Canonical Appearance Transformations Code to accompany our paper "How to Train a CAT: Learning Canonical Appearance Transformations
Minimal PyTorch implementation of Generative Latent Optimization from the paper "Optimizing the Latent Space of Generative Networks"
Minimal PyTorch implementation of Generative Latent Optimization This is a reimplementation of the paper Piotr Bojanowski, Armand Joulin, David Lopez-
Pytorch Implementation for CVPR2018 Paper: Learning to Compare: Relation Network for Few-Shot Learning
LearningToCompare Pytorch Implementation for Paper: Learning to Compare: Relation Network for Few-Shot Learning Howto download mini-imagenet and make
PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations"
Poincaré Embeddings for Learning Hierarchical Representations PyTorch implementation of Poincaré Embeddings for Learning Hierarchical Representations
PyTorch implementation of Trust Region Policy Optimization
PyTorch implementation of TRPO Try my implementation of PPO (aka newer better variant of TRPO), unless you need to you TRPO for some specific reasons.
This's an implementation of deepmind Visual Interaction Networks paper using pytorch
Visual-Interaction-Networks An implementation of Deepmind visual interaction networks in Pytorch. Introduction For the purpose of understanding the ch
Prototypical Networks for Few shot Learning in PyTorch
Prototypical Networks for Few shot Learning in PyTorch Simple alternative Implementation of Prototypical Networks for Few Shot Learning (paper, code)
Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation
Photographic Image Synthesis with Cascaded Refinement Networks-Pytorch (https://arxiv.org/abs/1707.09405) This is a Pytorch implementation of cascaded
A PyTorch Implementation of Neural IMage Assessment
NIMA: Neural IMage Assessment This is a PyTorch implementation of the paper NIMA: Neural IMage Assessment (accepted at IEEE Transactions on Image Proc
Style transfer, deep learning, feature transform
FastPhotoStyle License Copyright (C) 2018 NVIDIA Corporation. All rights reserved. Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons
Dilated RNNs in pytorch
PyTorch Dilated Recurrent Neural Networks PyTorch implementation of Dilated Recurrent Neural Networks (DilatedRNN). Getting Started Installation: $ pi
TensorFlow, PyTorch and Numpy layers for generating Orthogonal Polynomials
OrthNet TensorFlow, PyTorch and Numpy layers for generating multi-dimensional Orthogonal Polynomials 1. Installation 2. Usage 3. Polynomials 4. Base C
NIMA: Neural IMage Assessment
PyTorch NIMA: Neural IMage Assessment PyTorch implementation of Neural IMage Assessment by Hossein Talebi and Peyman Milanfar. You can learn more from
Sequence modeling benchmarks and temporal convolutional networks
Sequence Modeling Benchmarks and Temporal Convolutional Networks (TCN) This repository contains the experiments done in the work An Empirical Evaluati
This repository contains the source code and data for reproducing results of Deep Continuous Clustering paper
Deep Continuous Clustering Introduction This is a Pytorch implementation of the DCC algorithms presented in the following paper (paper): Sohil Atul Sh
PyTorch implementation of Progressive Growing of GANs for Improved Quality, Stability, and Variation.
PyTorch implementation of Progressive Growing of GANs for Improved Quality, Stability, and Variation. Warning: the master branch might collapse. To ob
Official Pytorch implementation of ICLR 2018 paper Deep Learning for Physical Processes: Integrating Prior Scientific Knowledge.
Deep Learning for Physical Processes: Integrating Prior Scientific Knowledge: Official Pytorch implementation of ICLR 2018 paper Deep Learning for Phy
PyTorch implementation of convolutional neural networks-based text-to-speech synthesis models
Deepvoice3_pytorch PyTorch implementation of convolutional networks-based text-to-speech synthesis models: arXiv:1710.07654: Deep Voice 3: Scaling Tex
YARR is Yet Another Robotics and Reinforcement learning framework for PyTorch.
Yet Another Robotics and Reinforcement (YARR) learning framework for PyTorch.
Yet Another Robotics and Reinforcement (YARR) learning framework for PyTorch.
Yet Another Robotics and Reinforcement (YARR) learning framework for PyTorch.
A Structured Self-attentive Sentence Embedding
Structured Self-attentive sentence embeddings Implementation for the paper A Structured Self-Attentive Sentence Embedding, which was published in ICLR
A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.
Use this instead: https://github.com/facebookresearch/maskrcnn-benchmark A Pytorch Implementation of Detectron Example output of e2e_mask_rcnn-R-101-F
Experiments with differentiable stacks and queues in PyTorch
Please use stacknn-core instead! StackNN This project implements differentiable stacks and queues in PyTorch. The data structures are implemented in s
Implementation of Multistream Transformers in Pytorch
Multistream Transformers Implementation of Multistream Transformers in Pytorch. This repository deviates slightly from the paper, where instead of usi
emoji-math computes the given python expression and returns either the value or the nearest 5 emojis as measured by cosine similarity.
emoji-math computes the given python expression and returns either the value or the nearest 5 emojis as measured by cosine similarity.
NLPShala , the best IDE for all Natural language processing tasks.
The revolutionary IDE for all NLP (Natural language processing) stuffs on the internet.
A curated list of amazingly awesome Cybersecurity datasets
A curated list of amazingly awesome Cybersecurity datasets
Easily turn single threaded command line applications into a fast, multi-threaded application with CIDR and glob support.
Easily turn single threaded command line applications into a fast, multi-threaded application with CIDR and glob support.
TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform
TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform
Pandas Machine Learning and Quant Finance Library Collection
Pandas Machine Learning and Quant Finance Library Collection
A command line tool to remove background from video and image
A command line tool to remove background from video and image, brought to you by BackgroundRemover.app which is an app made by nadermx powered by this tool
This repository contains some utilities for playing with PKINIT and certificates.
PKINIT tools This repository contains some utilities for playing with PKINIT and certificates. The tools are built on minikerberos and impacket. Accom
Implementation of H-Transformer-1D, Hierarchical Attention for Sequence Learning
H-Transformer-1D Implementation of H-Transformer-1D, Transformer using hierarchical Attention for sequence learning with subquadratic costs. For now,
[ICCV'21] PlaneTR: Structure-Guided Transformers for 3D Plane Recovery
PlaneTR: Structure-Guided Transformers for 3D Plane Recovery This is the official implementation of our ICCV 2021 paper News There maybe some bugs in
A Simple Telegram Bot By @AsmSafone to Download Files From Mega.nz and Upload It to Telegram
MegaDL-Bot A Simple Telegram Bot By @AsmSafone to Download Files From Mega.nz and Upload It to Telegram Features No Login Required All Mega.nz File Li
A Python-based application demonstrating various search algorithms, namely Depth-First Search (DFS), Breadth-First Search (BFS), and A* Search (Manhattan Distance Heuristic)
A Python-based application demonstrating various search algorithms, namely Depth-First Search (DFS), Breadth-First Search (BFS), and the A* Search (using the Manhattan Distance Heuristic)
Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.
Evidential Deep Learning for Guided Molecular Property Prediction and Discovery Ava Soleimany*, Alexander Amini*, Samuel Goldman*, Daniela Rus, Sangee
Write reproducible code for getting and processing ChEMBL
chembl_downloader Don't worry about downloading/extracting ChEMBL or versioning - just use chembl_downloader to write code that knows how to download
Set of utilities for exporting/controlling your robot in Blender
Blender Robotics Utils This repository contains utilities for exporting/controlling your robot in Blender Maintainers This repository is maintained by
Mventory is an API-driven solution for Makerspaces, Tinkerers, and Hackers.
Mventory is an API-driven inventory solution for Makers, Makerspaces, Hackspaces, and just about anyone else who needs to keep track of "stuff".
This is an online course where you can learn and master the skill of low-level performance analysis and tuning.
Performance Ninja Class This is an online course where you can learn to find and fix low-level performance issues, for example CPU cache misses and br
Code release for "Self-Tuning for Data-Efficient Deep Learning" (ICML 2021)
Self-Tuning for Data-Efficient Deep Learning This repository contains the implementation code for paper: Self-Tuning for Data-Efficient Deep Learning
Livemark is a static page generator that extends Markdown with interactive charts, tables, and more.
Livermark This software is in the early stages and is not well-tested Livemark is a static site generator that extends Markdown with interactive chart
Fetch Chrome, Firefox, WiFi password and system info
DISCLAIMER : OUR TOOLS ARE FOR EDUCATIONAL PURPOSES ONLY. DON'T USE THEM FOR ILLEGAL ACTIVITIES. YOU ARE THE ONLY RESPONSABLE FOR YOUR ACTIONS! OUR TO
MoviePy is a Python library for video editing, can read and write all the most common audio and video formats
MoviePy is a Python library for video editing: cutting, concatenations, title insertions, video compositing (a.k.a. non-linear editing), video processing, and creation of custom effects. See the gallery for some examples of use.
Portal is the fastest way to load and visualize your deep neural networks on images and videos 🔮
Portal is the fastest way to load and visualize your deep neural networks on images and videos 🔮
T2F: text to face generation using Deep Learning
⭐ [NEW] ⭐ T2F - 2.0 Teaser (coming soon ...) Please note that all the faces in the above samples are generated ones. The T2F 2.0 will be using MSG-GAN
Compute FID scores with PyTorch.
FID score for PyTorch This is a port of the official implementation of Fréchet Inception Distance to PyTorch. See https://github.com/bioinf-jku/TTUR f
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks (SDPoint) This repository contains the cod
PyTorch implementation of PNASNet-5 on ImageNet
PNASNet.pytorch PyTorch implementation of PNASNet-5. Specifically, PyTorch code from this repository is adapted to completely match both my implemetat
Hook Slinger acts as a simple service that lets you send, retry, and manage event-triggered POST requests, aka webhooks
Hook Slinger acts as a simple service that lets you send, retry, and manage event-triggered POST requests, aka webhooks. It provides a fully self-contained docker image that is easy to orchestrate, manage, and scale.
ReSSL: Relational Self-Supervised Learning with Weak Augmentation
ReSSL: Relational Self-Supervised Learning with Weak Augmentation This repository contains PyTorch evaluation code, training code and pretrained model
PyTorch implementation of popular datasets and models in remote sensing
PyTorch Remote Sensing (torchrs) (WIP) PyTorch implementation of popular datasets and models in remote sensing tasks (Change Detection, Image Super Re
Implementing SimCSE(paper, official repository) using TensorFlow 2 and KR-BERT.
KR-BERT-SimCSE Implementing SimCSE(paper, official repository) using TensorFlow 2 and KR-BERT. Training Unsupervised python train_unsupervised.py --mi
A Python interface between Earth Engine and xarray
eexarray A Python interface between Earth Engine and xarray Description eexarray was built to make processing gridded, mesoscale time series data quic
CobraML: Completely Customizable A python ML library designed to give the end user full control
CobraML: Completely Customizable What is it? CobraML is a python library built on both numpy and numba. Unlike other ML libraries CobraML gives the us
Vericopy - This Python script provides various usage modes for secure local file copying and hashing.
Vericopy This Python script provides various usage modes for secure local file copying and hashing. Hash data is captured and logged for paths before
Open-Source Toolkit for End-to-End Speech Recognition leveraging PyTorch-Lightning and Hydra.
🤗 Contributing to OpenSpeech 🤗 OpenSpeech provides reference implementations of various ASR modeling papers and three languages recipe to perform ta
Anomaly detection on SQL data warehouses and databases
With CueObserve, you can run anomaly detection on data in your SQL data warehouses and databases. Getting Started Install via Docker docker run -p 300
REST API for sentence tokenization and embedding using Multilingual Universal Sentence Encoder.
MUSE stands for Multilingual Universal Sentence Encoder - multilingual extension (supports 16 languages) of Universal Sentence Encoder (USE).
Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation", Haoxiang Wang, Han Zhao, Bo Li.
Bridging Multi-Task Learning and Meta-Learning Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Trainin
IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.
IDRLnet IDRLnet is a machine learning library on top of PyTorch. Use IDRLnet if you need a machine learning library that solves both forward and inver
Attractors is a package for simulation and visualization of strange attractors.
attractors Attractors is a package for simulation and visualization of strange attractors. Installation The simplest way to install the module is via
A python script to turn Ubuntu Desktop in a one stop security platform. The InfoSec Fortress installs the packages,tools, and resources to make Ubuntu 20.04 capable of both offensive and defensive security work.
infosec-fortress A python script to turn Ubuntu Desktop into a strong DFIR/RE System with some teeth (Purple Team Ops)! This is intended to create a s
A Telegram Bot to Play Audio in Voice Chats With Youtube and Deezer support. Supports Live streaming from youtube Supports Mega Radio Fm Streamings
Bot To Stream Musics on PyTGcalls with Channel Support. A Telegram Bot to Play Audio in Voice Chats With Supports Live streaming from youtube and Mega
Probe and discover HTTP pathname using brute-force methodology and filtered by specific word or 2 words at once
pathprober Probe and discover HTTP pathname using brute-force methodology and filtered by specific word or 2 words at once. Purpose Brute-forcing webs
CS583: Deep Learning
CS583: Deep Learning
Automated Integration Testing and Live Documentation for your API
Automated Integration Testing and Live Documentation for your API
RapidFuzz is a fast string matching library for Python and C++
RapidFuzz is a fast string matching library for Python and C++, which is using the string similarity calculations from FuzzyWuzzy
Code Release for Learning to Adapt to Evolving Domains
EAML Code release for "Learning to Adapt to Evolving Domains" (NeurIPS 2020) Prerequisites PyTorch = 0.4.0 (with suitable CUDA and CuDNN version) tor
Implementation of PyTorch-based multi-task pre-trained models
mtdp Library containing implementation related to the research paper "Multi-task pre-training of deep neural networks for digital pathology" (Mormont
Codes accompanying the paper "Learning Nearly Decomposable Value Functions with Communication Minimization" (ICLR 2020)
NDQ: Learning Nearly Decomposable Value Functions with Communication Minimization Note This codebase accompanies paper Learning Nearly Decomposable Va
Official code for UnICORNN (ICML 2021)
UnICORNN (Undamped Independent Controlled Oscillatory RNN) [ICML 2021] This repository contains the implementation to reproduce the numerical experime
ICML 21 - Voice2Series: Reprogramming Acoustic Models for Time Series Classification
Voice2Series-Reprogramming Voice2Series: Reprogramming Acoustic Models for Time Series Classification International Conference on Machine Learning (IC
Deep Two-View Structure-from-Motion Revisited
Deep Two-View Structure-from-Motion Revisited This repository provides the code for our CVPR 2021 paper Deep Two-View Structure-from-Motion Revisited.
The official PyTorch code for 'DER: Dynamically Expandable Representation for Class Incremental Learning' accepted by CVPR2021
DER.ClassIL.Pytorch This repo is the official implementation of DER: Dynamically Expandable Representation for Class Incremental Learning (CVPR 2021)
Spatial Contrastive Learning for Few-Shot Classification (SCL)
This repo contains the official implementation of Spatial Contrastive Learning for Few-Shot Classification (SCL), which presents of a novel contrastive learning method applied to few-shot image classification in order to learn more general purpose embeddings, and facilitate the test-time adaptation to novel visual categories.
Moment-DETR code and QVHighlights dataset
Moment-DETR QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries Jie Lei, Tamara L. Berg, Mohit Bansal For dataset de
TilinGNN: Learning to Tile with Self-Supervised Graph Neural Network (SIGGRAPH 2020)
TilinGNN: Learning to Tile with Self-Supervised Graph Neural Network (SIGGRAPH 2020) About The goal of our research problem is illustrated below: give
Implementation of CVPR 2020 Dual Super-Resolution Learning for Semantic Segmentation
Dual super-resolution learning for semantic segmentation 2021-01-02 Subpixel Update Happy new year! The 2020-12-29 update of SISR with subpixel conv p
PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.
VAENAR-TTS - PyTorch Implementation PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.