Python Data-efficient-gan-training Resources

Transformers Optimus's transformation plugins are implementations of Task and Hook interfaces that allows execution of arbitrary jobs in optimus. To i

Minimal Ethereum fee data viewer for the terminal, contained in a single python script. Connects to your node and displays some metrics in real-time.

CDK Pipelines for Data Lake Infrastructure Deployment This solution helps you deploy data lake infrastructure on AWS using CDK Pipelines. This is base

MUST-GAN Code | paper The Pytorch implementation of our CVPR2021 paper "MUST-GAN: Multi-level Statistics Transfer for Self-driven Person Image Generat

Auto-Complete Google Project In this project there is an implementation for one feature of Google's search engines - AutoComplete. Autocomplete, or wo

Proteno This is the data release associated with the corresponding NAACL 2021 Paper - Proteno: Text Normalization with Limited Data for Fast Deploymen

ManiSkill-Learn ManiSkill-Learn is a framework for training agents on SAPIEN Open-Source Manipulation Skill Challenge, a large-scale learning-from-dem

Introduction Code and data for ACL 2021 Paper "Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning". We cons

TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks This is a Python3 / Pytorch implementation of TadGAN paper. The associated

OpenGAN: Open-Set Recognition via Open Data Generation ICCV 2021 (oral) Real-world machine learning systems need to analyze novel testing data that di

SemCo The official pytorch implementation of the paper All Labels Are Not Created Equal: Enhancing Semi-supervision via Label Grouping and Co-training

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

Epistemic Neural Networks A library for uncertainty representation and training in neural networks. Introduction Many applications in deep learning re

Update (20 Jan 2020): MODALS on text data is avialable MODALS MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space Table of Conte

Active Testing: Sample-Efficient Model Evaluation Hi, good to see you here! 👋 This is code for "Active Testing: Sample-Efficient Model Evaluation". P

Thailand COVID-19 Cluster Data Extraction About Extract Clusters from Thailand Daily COVID-19 briefing PDF Download latest data Here. Data will be upd

Demo BERT ONNX pipeline written in rust This demo showcase the use of onnxruntime-rs with a GPU on CUDA 11 to run Bert in a data pipeline with Rust. R

Kunyu(坤舆) - More efficient corporate asset collection English | 中文文档 0x00 Introduce Tool introduction Kunyu (kunyu), whose name is taken from , is act

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

MASS: Masked Sequence to Sequence Pre-training for Language Generation

Collect super-resolution related papers, data, repositories

crypto-performance-tracker Use this script to track the gains of cryptocurrencies using historical data and display it on a super-imposed chart in ord

The Researcher COVID data Automated data scraper for Thailand COVID-19 data Accessing the Data 1st Dose Provincial Vaccination Data 2nd Dose Provincia

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

Random Erasing Data Augmentation =============================================================== black white random This code has the source code for

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

In-Place Activated BatchNorm In-Place Activated BatchNorm for Memory-Optimized Training of DNNs In-Place Activated BatchNorm (InPlace-ABN) is a novel

Bottom-Up and Top-Down Attention for Visual Question Answering An efficient PyTorch implementation of the winning entry of the 2017 VQA Challenge. The

PyTorch implementation of VAGAN: Visual Feature Attribution Using Wasserstein GANs This code aims to reproduce results obtained in the paper "Visual F

Efficient Neural Architecture Search (ENAS) in PyTorch PyTorch implementation of Efficient Neural Architecture Search via Parameters Sharing. ENAS red

Proximal Backpropagation Proximal Backpropagation (ProxProp) is a neural network training algorithm that takes implicit instead of explicit gradient s

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. Warning: the master branch might collapse. To ob

This repository has gone stale as I unfortunately do not have the time to maintain it anymore. If you would like to continue the development of it as

Use this instead: https://github.com/facebookresearch/maskrcnn-benchmark A Pytorch Implementation of Detectron Example output of e2e_mask_rcnn-R-101-F

A curated list of amazingly awesome Cybersecurity datasets

A python application for manipulating pandas data frames from the comfort of your web browser. Data flows are represented as a Directed Acyclic Graph, and nodes can be ran individually as the user sees fit.

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

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

LARGE: Latent-Based Regression through GAN Semantics [Project Website] [Google Colab] [Paper] LARGE: Latent-Based Regression through GAN Semantics Yot

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

LTP: Learned Token Pruning for Transformers Check our paper for more details. Installation We follow the same installation procedure as the original H

DataFree A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation" Authors: Gongfa

Deduplicating Training Data Makes Language Models Better This repository contains code to deduplicate language model datasets as descrbed in the paper

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

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

ViTGAN: Training GANs with Vision Transformers A PyTorch implementation of ViTGAN based on paper ViTGAN: Training GANs with Vision Transformers. Refer

Pynixutil - Utility functions for working with data from Nix in Python Examples Base32 encoding/decoding import pynixutil input = "v5sv61sszx301i0x6x

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.

NeuralCompression is a Python repository dedicated to research of neural networks that compress data. The repository includes tools such as JAX-based entropy coders, image compression models, video compression models, and metrics for image and video evaluation.

Open-source tool for exploring, labeling, and monitoring data for AI projects

Advanced Deep Learning with TensorFlow 2 and Keras (Updated for 2nd Edition)

A PyTorch Reproduction of HCN Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation. Ch

Overview PyTorch 0.4.1 | Python 3.6.5 Annotated implementations with comparative introductions for minimax, non-saturating, wasserstein, wasserstein g

DiffAI v3 DiffAI is a system for training neural networks to be provably robust and for proving that they are robust. The system was developed for the

DrQ-v2: Improved Data-Augmented RL Agent Method DrQ-v2 is a model-free off-policy algorithm for image-based continuous control. DrQ-v2 builds on DrQ,

Pandas Tab Implementation of Stata's tabulate command in Pandas for extremely easy to type one-way and two-way tabulations. Support: Python 3.7 and 3.

Knockoff Factory A library for generating mock data and creating database fixtures that can be used for unit testing. Table of content Installation Ch

Parallelformers: An Efficient Model Parallelization Toolkit for Deployment

ClusterGCN ⠀⠀ A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019). A

LiDAR-MOS: Moving Object Segmentation in 3D LiDAR Data This repo contains the code for our paper: Moving Object Segmentation in 3D LiDAR Data: A Learn

GIANT Code and data for paper "GIANT: Scalable Creation of a Web-scale Ontology" https://arxiv.org/pdf/2004.02118.pdf Please cite our paper if this pr

Self-training for Few-shot Transfer Across Extreme Task Differences (STARTUP) Introduction This repo contains the official implementation of the follo

The Power of Scale for Parameter-Efficient Prompt Tuning Implementation of soft embeddings from https://arxiv.org/abs/2104.08691v1 using Pytorch and H

Adam-NSCL This is a PyTorch implementation of Adam-NSCL algorithm for continual learning from our CVPR2021 (oral) paper: Title: Training Networks in N

Random Shadows and Highlights This repo has the source code for the paper: Random Shadows and Highlights: A new data augmentation method for extreme l

Efficient Self-Supervised Vision Transformers (EsViT) PyTorch implementation for EsViT, built with two techniques: A multi-stage Transformer architect

StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking Datasets You can download datasets that have been pre-pr

Computationally Efficient Optimization of Plackett-Luce Ranking Models for Relevance and Fairness This repository contains the code used for the exper

RawVSR This repo contains the official codes for our paper: Exploit Camera Raw Data for Video Super-Resolution via Hidden Markov Model Inference Xiaoh

neural waveshaping synthesis real-time neural audio synthesis in the waveform domain paper • website • colab • audio by Ben Hayes, Charalampos Saitis,

MidiBERT-Piano Authors: Yi-Hui (Sophia) Chou, I-Chun (Bronwin) Chen Introduction This is the official repository for the paper, MidiBERT-Piano: Large-

AlphaNet: Improved Training of Supernet with Alpha-Divergence This repository contains our PyTorch training code, evaluation code and pretrained model

LiDAR R-CNN: An Efficient and Universal 3D Object Detector Introduction This is the official code of LiDAR R-CNN: An Efficient and Universal 3D Object

Accelerate PyTorch models with ONNX Runtime

Using python and scikit-learn to make stock predictions

Решения и подсказки к тренировке по алгоритмам от Яндекса Что есть внутри Решения с подсказками и комментариями; рекомендую сначала смотреть md файл п

​ DS2.ai is an integrated AI operation solution that supports all stages from custom AI development to deployment. It is an AI-specialized platform service that collects data, builds a training dataset through data labeling, and enables automatic development of artificial intelligence and easy deployment and operation.

Raganarok X Data Dump Raganarok X: Next Generation Data Dump More interesting Files File Name Contains en_langs All the variables you need in English

A Python library for reading, writing and visualizing the OMEGA Format, targeted towards storing reference and perception data in the automotive context on an object list basis with a focus on an urban use case.

Squidpy is a tool for the analysis and visualization of spatial molecular data. It builds on top of scanpy and anndata, from which it inherits modularity and scalability. It provides analysis tools that leverages the spatial coordinates of the data, as well as tissue images if available.

S2-BNN (Self-supervised Binary Neural Networks Using Distillation Loss) This is the official pytorch implementation of our paper: "S2-BNN: Bridging th

Generative Models Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow. Also present here are RBM and Helmholtz Machine. Note: Gen

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

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.

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

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

XGBoost-Ray is a distributed backend for XGBoost, built on top of distributed computing framework Ray.

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

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