Python Kata-Clean-Machine-Learning-From-Dirty-Code Resources

Object-aware Contrastive Learning Official PyTorch implementation of "Object-aware Contrastive Learning for Debiased Scene Representation" by Sangwoo

Scriptfab - What is it? A python script to prefab your scripts/text files, and re create them with ease and not have to open your browser to copy code

CrossFormer This repository is the code for our paper CrossFormer: A Versatile Vision Transformer Based on Cross-scale Attention. Introduction Existin

UnivNet UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation This is an unofficial PyTorch

背景 安装教程 快速上手 （一）预训练模型 （二）机器翻译 （三）文本分类 TenTrans 进阶 1. 多语言机器翻译 2. 跨语言预训练 背景 TrenTrans是一个统一的端到端的多语言多任务预训练平台，支持多种预训练方式，以及序列生成和自然语言理解任务。 安装教程 git clone git

Evidently helps analyze machine learning models during validation or production monitoring. The tool generates interactive visual reports and JSON profiles from pandas DataFrame or csv files. Currently 6 reports are available.

🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

Active Learning allows you to efficiently label training data in a small-data scenario.

40 Algorithms Every Programmer Should Know, published by Packt

Off-Policy Multi-Agent Reinforcement Learning (MARL) Algorithms This repository contains implementations of various off-policy multi-agent reinforceme

Interpretable Machine Learning with Python, published by Packt

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 The codes were used for the paper meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting (ICML 2017) [pdf]

Gradient Episodic Memory for Continual Learning Source code for the paper: @inproceedings{GradientEpisodicMemory, title={Gradient Episodic Memory

DeblurGAN arXiv Paper Version Pytorch implementation of the paper DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks. Our netwo

Dynamic Routing Between Capsules - PyTorch implementation PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules from Sara Sabour,

CondenseNets This repository contains the code (in PyTorch) for "CondenseNet: An Efficient DenseNet using Learned Group Convolutions" paper by Gao Hua

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

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.

pix2pixHD Project | Youtube | Paper Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic image-to-image translatio

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 The YOLOv2 is one of the most popular one-stage object detector. This project adopts PyTorc

PyTorch Realtime Multi-Person Pose Estimation This is a pytorch version of Realtime_Multi-Person_Pose_Estimation, origin code is here Realtime_Multi-P

Interaction-Network-Pytorch Pytorch Implementraion of Interaction Networks for Learning about Objects, Relations and Physics. Interaction Network is a

Unofficial PyTorch implementation of "Zero-Shot" Super-Resolution using Deep Internal Learning Unofficial Implementation of 1712.06087 "Zero-Shot" Sup

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

Gated-Attention Architectures for Task-Oriented Language Grounding This is a PyTorch implementation of the AAAI-18 paper: Gated-Attention Architecture

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 This is a reimplementation of the paper Piotr Bojanowski, Armand Joulin, David Lopez-

LearningToCompare Pytorch Implementation for Paper: Learning to Compare: Relation Network for Few-Shot Learning Howto download mini-imagenet and make

Poincaré Embeddings for Learning Hierarchical Representations PyTorch implementation of Poincaré Embeddings for Learning Hierarchical Representations

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.

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 Simple alternative Implementation of Prototypical Networks for Few Shot Learning (paper, code)

Photographic Image Synthesis with Cascaded Refinement Networks-Pytorch (https://arxiv.org/abs/1707.09405) This is a Pytorch implementation of cascaded

NIMA: Neural IMage Assessment This is a PyTorch implementation of the paper NIMA: Neural IMage Assessment (accepted at IEEE Transactions on Image Proc

FastPhotoStyle License Copyright (C) 2018 NVIDIA Corporation. All rights reserved. Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons

Pytorch ReID Strong, Small, Friendly A tiny, friendly, strong baseline code for Person-reID (based on pytorch). Strong. It is consistent with the new

PyTorch Dilated Recurrent Neural Networks PyTorch implementation of Dilated Recurrent Neural Networks (DilatedRNN). Getting Started Installation: $ pi

i-RevNet: Deep Invertible Networks Pytorch implementation of i-RevNets. i-RevNets define a family of fully invertible deep networks, built from a succ

PyTorch NIMA: Neural IMage Assessment PyTorch implementation of Neural IMage Assessment by Hossein Talebi and Peyman Milanfar. You can learn more from

Deep Continuous Clustering Introduction This is a Pytorch implementation of the DCC algorithms presented in the following paper (paper): Sohil Atul Sh

PackNet: https://arxiv.org/abs/1711.05769 Pretrained models are available here: https://uofi.box.com/s/zap2p03tnst9dfisad4u0sfupc0y1fxt Datasets in Py

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

Deep Learning for Physical Processes: Integrating Prior Scientific Knowledge: Official Pytorch implementation of ICLR 2018 paper Deep Learning for Phy

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

refactor is an end-to-end refactoring framework that is built on top of the 'simple but effective refactorings' assumption. It is much easier to write a simple script with it rather than trying to figure out what sort of a regex you need in order to replace a pattern (if it is even matchable with regexes).

Yet Another Robotics and Reinforcement (YARR) learning framework for PyTorch.

Yet Another Robotics and Reinforcement (YARR) learning framework for PyTorch.

AccSGD This is the code associated with Accelerated SGD algorithm used in the paper On the insufficiency of existing momentum schemes for Stochastic O

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

Emergent Translation in Multi-Agent Communication PyTorch implementation of the models described in the paper Emergent Translation in Multi-Agent Comm

Multistream Transformers Implementation of Multistream Transformers in Pytorch. This repository deviates slightly from the paper, where instead of usi

Visual Saliency Transformer (VST) source code for our ICCV 2021 paper “Visual Saliency Transformer” by Nian Liu, Ni Zhang, Kaiyuan Wan, Junwei Han, an

The revolutionary IDE for all NLP (Natural language processing) stuffs on the internet.

A curated list of amazingly awesome Cybersecurity datasets

TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform

Pandas Machine Learning and Quant Finance Library Collection

H-Transformer-1D Implementation of H-Transformer-1D, Transformer using hierarchical Attention for sequence learning with subquadratic costs. For now,

PlaneTR: Structure-Guided Transformers for 3D Plane Recovery This is the official implementation of our ICCV 2021 paper News There maybe some bugs in

Evidential Deep Learning for Guided Molecular Property Prediction and Discovery Ava Soleimany*, Alexander Amini*, Samuel Goldman*, Daniela Rus, Sangee

chembl_downloader Don't worry about downloading/extracting ChEMBL or versioning - just use chembl_downloader to write code that knows how to download

Self-Tuning for Data-Efficient Deep Learning This repository contains the implementation code for paper: Self-Tuning for Data-Efficient 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

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 (SDPoint) This repository contains the cod

GAN stability This repository contains the experiments in the supplementary material for the paper Which Training Methods for GANs do actually Converg

PNASNet.pytorch PyTorch implementation of PNASNet-5. Specifically, PyTorch code from this repository is adapted to completely match both my implemetat

Human Pose Regression with Residual Log-likelihood Estimation [Paper] [arXiv] [Project Page] Human Pose Regression with Residual Log-likelihood Estima

ReSSL: Relational Self-Supervised Learning with Weak Augmentation This repository contains PyTorch evaluation code, training code and pretrained model

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

GPT-Code-Clippy (GPT-CC) is an open source version of GitHub Copilot, a language model -- based on GPT-3, called GPT-Codex -- that is fine-tuned on publicly available code from GitHub.

MUSE stands for Multilingual Universal Sentence Encoder - multilingual extension (supports 16 languages) of Universal Sentence Encoder (USE).

Bridging Multi-Task Learning and Meta-Learning Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Trainin

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

Django Sage Painless The django-sage-painless is a valuable package based on Django Web Framework & Django Rest Framework for high-level and rapid web

Code for Text Prior Guided Scene Text Image Super-Resolution

CS583: Deep Learning

EAML Code release for "Learning to Adapt to Evolving Domains" (NeurIPS 2020) Prerequisites PyTorch = 0.4.0 (with suitable CUDA and CuDNN version) tor

NDQ: Learning Nearly Decomposable Value Functions with Communication Minimization Note This codebase accompanies paper Learning Nearly Decomposable Va

UnICORNN (Undamped Independent Controlled Oscillatory RNN) [ICML 2021] This repository contains the implementation to reproduce the numerical experime

Voice2Series-Reprogramming Voice2Series: Reprogramming Acoustic Models for Time Series Classification International Conference on Machine Learning (IC

Deep Two-View Structure-from-Motion Revisited This repository provides the code for our CVPR 2021 paper Deep Two-View Structure-from-Motion Revisited.

DER.ClassIL.Pytorch This repo is the official implementation of DER: Dynamically Expandable Representation for Class Incremental Learning (CVPR 2021)

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 QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries Jie Lei, Tamara L. Berg, Mohit Bansal For dataset de

Riggable 3D Face Reconstruction via In-Network Optimization Source code for CVPR 2021 paper "Riggable 3D Face Reconstruction via In-Network Optimizati

TilinGNN: Learning to Tile with Self-Supervised Graph Neural Network (SIGGRAPH 2020) About The goal of our research problem is illustrated below: give

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

VAENAR-TTS - PyTorch Implementation PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.

Towards Understanding and Mitigating Social Biases in Language Models This repo contains code and data for evaluating and mitigating bias from generat

This package creates clean and beautiful matplotlib plots that work on light and dark backgrounds. Inspired by the work of Edward Tufte.

This repository is a toolkit to do machine learning for programming languages. It implements tokenization, dataset preprocessing, model training and m

Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set —— PyTorch implementation This is an unofficial offici

SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo Thomas Kollar, Michael Laskey, Kevin Stone, Brijen Thananjeyan

Triangle Multiplicative Module - Pytorch Implementation of the Triangle Multiplicative module, used in Alphafold2 as an efficient way to mix rows or c

neraug This python library helps you with augmenting text data for named entity recognition. Augmentation Example Reference from An Analysis of Simple

NeuralWOZ This code is official implementation of "NeuralWOZ: Learning to Collect Task-Oriented Dialogue via Model-based Simulation". Sungdong Kim, Mi

AlphaFold This package provides an implementation of the inference pipeline of AlphaFold v2.0. This is a completely new model that was entered in CASP

This library was developed in order to facilitate rapid prototyping in Python of predictive machine-learning models using longitudinal medical data from an OMOP CDM-standard database.