3624 Repositories
Python neural-machine-translation Libraries
Parameterized Explainer for Graph Neural Network
PGExplainer This is a Tensorflow implementation of the paper: Parameterized Explainer for Graph Neural Network https://arxiv.org/abs/2011.04573 NeurIP
MachineLearningStocks is designed to be an intuitive and highly extensible template project applying machine learning to making stock predictions.
Using python and scikit-learn to make stock predictions
Automated machine learning: Review of the state-of-the-art and opportunities for healthcare
Automated machine learning: Review of the state-of-the-art and opportunities for healthcare
Implementation of "Glancing Transformer for Non-Autoregressive Neural Machine Translation"
GLAT Implementation for the ACL2021 paper "Glancing Transformer for Non-Autoregressive Neural Machine Translation" Requirements Python = 3.7 Pytorch
The MLOps platform for innovators π
β 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.
Write Python in Urdu - Ψ§Ψ±Ψ―Ω Ω ΫΪΊ Ϊ©ΩΪ ΩΪ©ΪΎΫΪΊ
UrduPython Write simple Python in Urdu. How to Use Write Urdu code in Ψ³Ψ§Ω ΩΎΩΫΩΎΫ The mappings are as following: "Ϋ": ".", "Ψ":
Lags valorant servers by rapidly picking up and throwing shorties.
Lags valorant servers by rapidly picking up and throwing shorties.
code for "AttentiveNAS Improving Neural Architecture Search via Attentive Sampling"
code for "AttentiveNAS Improving Neural Architecture Search via Attentive Sampling"
A collection of research papers and software related to explainability in graph machine learning.
A collection of research papers and software related to explainability in graph machine learning.
A collection of 100 Deep Learning images and visualizations
A collection of Deep Learning images and visualizations. The project has been developed by the AI Summer team and currently contains almost 100 images.
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)
S2-BNN (Self-supervised Binary Neural Networks Using Distillation Loss) This is the official pytorch implementation of our paper: "S2-BNN: Bridging th
[CVPR 2021] A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts
Visual-Reasoning-eXplanation [CVPR 2021 A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts] Project Page | Vid
A collection of 100 Deep Learning images and visualizations
A collection of Deep Learning images and visualizations. The project has been developed by the AI Summer team and currently contains almost 100 images.
Cancer metastasis detection with neural conditional random field (NCRF)
NCRF Prerequisites Data Whole slide images Annotations Patch images Model Training Testing Tissue mask Probability map Tumor localization FROC evaluat
A PyTorch implementation of " EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks."
EfficientNet A PyTorch implementation of EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. [arxiv] [Official TF Repo] Implemen
This repo contains the official implementations of EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis
EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis This repo contains the official implementations of EigenDamage: Structured Prunin
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening Introduction This is an implementation of the model used for breast
π€ A Python library for learning and evaluating knowledge graph embeddings
PyKEEN PyKEEN (Python KnowlEdge EmbeddiNgs) is a Python package designed to train and evaluate knowledge graph embedding models (incorporating multi-m
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
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
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
Generative Models Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow. Also present here are RBM and Helmholtz Machine. Note: Gen
Draw like Bob Ross using the power of Neural Networks (With PyTorch)!
Draw like Bob Ross using the power of Neural Networks! (+ Pytorch) Learning Process Visualization Getting started Install dependecies Requires python3
A community run, 5-day PyTorch Deep Learning Bootcamp
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 with lots of PyTorch tricks
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: Deep learning person re-identification in PyTorch.
Torchreid Torchreid is a library for deep-learning person re-identification, written in PyTorch. It features: multi-GPU training support both image- a
Tensors and neural networks in Haskell
Hasktorch Hasktorch is a library for tensors and neural networks in Haskell. It is an independent open source community project which leverages the co
PyTorch - Python + Nim
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+
Kaggle | 9th place single model solution for TGS Salt Identification Challenge
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.
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.
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.
Rust bindings for the C++ api of PyTorch.
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
π All-in-one web-based IDE specialized for machine learning and data science.
All-in-one web-based development environment for machine learning Getting Started β’ Features & Screenshots β’ Support β’ Report a Bug β’ FAQ β’ Known Issu
Geometry-Consistent Neural Shape Representation with Implicit Displacement Fields
Geometry-Consistent Neural Shape Representation with Implicit Displacement Fields [project page][paper][cite] Geometry-Consistent Neural Shape Represe
An AI Assistant More Than a Toolkit
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
Gesture-controlled Video Game. Just swing your finger and play the game without touching your PC
Gesture Controlled Video Game Detailed Blog : https://www.analyticsvidhya.com/blog/2021/06/gesture-controlled-video-game/ Introduction This project is
HyperPose is a library for building high-performance custom pose estimation applications.
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.
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.
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
PyTorch implementation of Densely Connected Time Delay Neural Network
Densely Connected Time Delay Neural Network PyTorch implementation of Densely Connected Time Delay Neural Network (D-TDNN) in our paper "Densely Conne
NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling @ INTERSPEECH 2021 Accepted
NU-Wave β Official PyTorch Implementation NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling Junhyeok Lee, Seungu Han @ MINDsLab Inc
Neural Logic Inductive Learning
Neural Logic Inductive Learning This is the implementation of the Neural Logic Inductive Learning model (NLIL) proposed in the ICLR 2020 paper: Learn
Code release for DS-NeRF (Depth-supervised Neural Radiance Fields)
Depth-supervised NeRF: Fewer Views and Faster Training for Free Project | Paper | YouTube Pytorch implementation of our method for learning neural rad
Official PyTorch implementation of "Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets" (ICLR 2021)
Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets This is the official PyTorch implementation for the paper Rapid Neural A
Code for paper "Vocabulary Learning via Optimal Transport for Neural Machine Translation"
**Codebase and data are uploaded in progress. ** VOLT(-py) is a vocabulary learning codebase that allows researchers and developers to automaticaly ge
A PyTorch-based open-source framework that provides methods for improving the weakly annotated data and allows researchers to efficiently develop and compare their own methods.
Knodle (Knowledge-supervised Deep Learning Framework) - a new framework for weak supervision with neural networks. It provides a modularization for se
π€ Push your spaCy pipelines to the Hugging Face Hub
spacy-huggingface-hub: Push your spaCy pipelines to the Hugging Face Hub This package provides a CLI command for uploading any trained spaCy pipeline
Translation for Trilium Notes. Trilium Notes δΈζη.
Trilium Translation δΈζθ―΄ζ This repo provides a translation for the awesome Trilium Notes. Currently, I have translated Trilium Notes into Chinese. Test
MooGBT is a library for Multi-objective optimization in Gradient Boosted Trees.
MooGBT is a library for Multi-objective optimization in Gradient Boosted Trees. MooGBT optimizes for multiple objectives by defining constraints on sub-objective(s) along with a primary objective. The constraints are defined as upper bounds on sub-objective loss function. MooGBT uses a Augmented Lagrangian(AL) based constrained optimization framework with Gradient Boosted Trees, to optimize for multiple objectives.
Official PyTorch implementation of the preprint paper "Stylized Neural Painting", accepted to CVPR 2021.
Official PyTorch implementation of the preprint paper "Stylized Neural Painting", accepted to CVPR 2021.
This machine-learning algorithm takes in data from the last 60 days and tries to predict tomorrow's price of any crypto you ask it.
Crypto-Currency-Predictor This machine-learning algorithm takes in data from the last 60 days and tries to predict tomorrow's price of any crypto you
Classify bird species based on their songs using SIamese Networks and 1D dilated convolutions.
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.
Use different orders of N-gram model to play Hangman game.
Hangman game The Hangman game is a game whereby one person thinks of a word, which is kept secret from another person, who tries to guess the word one
Pose Detection and Machine Learning for real-time body posture analysis during exercise to provide audiovisual feedback on improvement of form.
Posture: Pose Tracking and Machine Learning for prescribing corrective suggestions to improve posture and form while exercising. This repository conta
This is my reading list for my PhD in AI, NLP, Deep Learning and more.
This is my reading list for my PhD in AI, NLP, Deep Learning and more.
mlscraper: Scrape data from HTML pages automatically with Machine Learning
π€ Scrape data from HTML websites automatically with Machine Learning
This is the source code for our ICLR2021 paper: Adaptive Universal Generalized PageRank Graph Neural Network.
GPRGNN This is the source code for our ICLR2021 paper: Adaptive Universal Generalized PageRank Graph Neural Network. Hidden state feature extraction i
Code for the paper "Balancing Training for Multilingual Neural Machine Translation, ACL 2020"
Balancing Training for Multilingual Neural Machine Translation Implementation of the paper Balancing Training for Multilingual Neural Machine Translat
[ACL 20] Probing Linguistic Features of Sentence-level Representations in Neural Relation Extraction
REval Table of Contents Introduction Overview Requirements Installation Probing Usage Citation License π Introduction REval is a simple framework for
Kaggle | 9th place (part of) solution for the Bristol-Myers Squibb β Molecular Translation challenge
Part of the 9th place solution for the Bristol-Myers Squibb β Molecular Translation challenge translating images containing chemical structures into I
Code for the paper "Implicit Representations of Meaning in Neural Language Models"
Implicit Representations of Meaning in Neural Language Models Preliminaries Create and set up a conda environment as follows: conda create -n state-pr
Automated modeling and machine learning framework FEDOT
This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML). It can build custom modeling pipelines for different real-world processes in an automated way using an evolutionary approach. FEDOT supports classification (binary and multiclass), regression, clustering, and time series prediction tasks.
Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Machine Learning
Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Machine Learning
R-Drop: Regularized Dropout for Neural Networks
R-Drop: Regularized Dropout for Neural Networks R-drop is a simple yet very effective regularization method built upon dropout, by minimizing the bidi
PyTorch Implementation of NCSOFT's FastPitchFormant: Source-filter based Decomposed Modeling for Speech Synthesis
FastPitchFormant - PyTorch Implementation PyTorch Implementation of FastPitchFormant: Source-filter based Decomposed Modeling for Speech Synthesis. Qu
An Efficient Implementation of Analytic Mesh Algorithm for 3D Iso-surface Extraction from Neural Networks
AnalyticMesh Analytic Marching is an exact meshing solution from neural networks. Compared to standard methods, it completely avoids geometric and top
SIMULEVAL A General Evaluation Toolkit for Simultaneous Translation
SimulEval SimulEval is a general evaluation framework for simultaneous translation on text and speech. Requirement python = 3.7.0 Installation git cl
Machine Unlearning with SISA
Machine Unlearning with SISA Lucas Bourtoule, Varun Chandrasekaran, Christopher Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, N
Official repository for the paper "Going Beyond Linear Transformers with Recurrent Fast Weight Programmers"
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
PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing
pure-predict: Machine learning prediction in pure Python
pure-predict speeds up and slims down machine learning prediction applications. It is a foundational tool for serverless inference or small batch prediction with popular machine learning frameworks like scikit-learn and fasttext. It implements the predict methods of these frameworks in pure Python.
Graph4nlp is the library for the easy use of Graph Neural Networks for NLP
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).
PyTorch implementation of ARM-Net: Adaptive Relation Modeling Network for Structured Data.
A ready-to-use framework of latest models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, and etc.
A python library to build Model Trees with Linear Models at the leaves.
A python library to build Model Trees with Linear Models at the leaves.
A data preprocessing package for time series data. Design for machine learning and deep learning.
A data preprocessing package for time series data. Design for machine learning and deep learning.
This is a template for the Non-autoregressive Deep Learning-Based TTS model (in PyTorch).
Non-autoregressive Deep Learning-Based TTS Template This is a template for the Non-autoregressive TTS model. It contains Data Preprocessing Pipeline D
Meerkat provides fast and flexible data structures for working with complex machine learning datasets.
Meerkat makes it easier for ML practitioners to interact with high-dimensional, multi-modal data. It provides simple abstractions for data inspection, model evaluation and model training supported by efficient and robust IO under the hood.
EdMIPS: Rethinking Differentiable Search for Mixed-Precision Neural Networks
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.
Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021
SNN_Calibration Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021 Feature Comparison of SNN calibration: Features SNN Direct Tr
This repository contains a PyTorch implementation of "AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis".
AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis | Project Page | Paper | PyTorch implementation for the paper "AD-NeRF: Audio
AllenNLP integration for Shiba: Japanese CANINE model
Allennlp Integration for Shiba allennlp-shiab-model is a Python library that provides AllenNLP integration for shiba-model. SHIBA is an approximate re
Gamestonk Terminal is an awesome stock and crypto market terminal
Gamestonk Terminal is an awesome stock and crypto market terminal. A FOSS alternative to Bloomberg Terminal.
30 Days Of Machine Learning Using Pytorch
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
PyTorch implementation of Soft-DTW: a Differentiable Loss Function for Time-Series in CUDA
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
Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch
Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch
Craxk is a SINGLE AND NON-REPLICABLE Hash that uses data from the hardware where it is executed to form a hash that can only be reproduced by a single machine.
What is Craxk ? Craxk is a UNIQUE AND NON-REPLICABLE Hash that uses data from the hardware where it is executed to form a hash that can only be reprod
Orthogonal Over-Parameterized Training
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 is an extension of ProbLog that integrates Probabilistic Logic Programming with deep learning by introducing the neural predicate.
DeepProbLog DeepProbLog is an extension of ProbLog that integrates Probabilistic Logic Programming with deep learning by introducing the neural predic
Grapheme-to-phoneme (G2P) conversion is the process of generating pronunciation for words based on their written form.
Neural G2P to portuguese language Grapheme-to-phoneme (G2P) conversion is the process of generating pronunciation for words based on their written for
BRepNet: A topological message passing system for solid models
BRepNet: A topological message passing system for solid models This repository contains the an implementation of BRepNet: A topological message passin
PyTorch Implementation of Google Brain's WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis
WaveGrad2 - PyTorch Implementation PyTorch Implementation of Google Brain's WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis. Status (202
SmartSim Infrastructure Library.
Home Install Documentation Slack Invite Cray Labs SmartSim SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and Ten
[ICML 2021] Break-It-Fix-It: Learning to Repair Programs from Unlabeled Data
Break-It-Fix-It: Learning to Repair Programs from Unlabeled Data This repo provides the source code & data of our paper: Break-It-Fix-It: Unsupervised
Spatially-Adaptive Pixelwise Networks for Fast Image Translation, CVPR 2021
Image Translation with ASAPNets Spatially-Adaptive Pixelwise Networks for Fast Image Translation, CVPR 2021 Webpage | Paper | Video Installation insta
MetaBalance: High-Performance Neural Networks for Class-Imbalanced Data
This repository is the official PyTorch implementation of Meta-Balance. Find the paper on arxiv MetaBalance: High-Performance Neural Networks for Clas
Learning Neural Network Subspaces
Learning Neural Network Subspaces Welcome to the codebase for Learning Neural Network Subspaces by Mitchell Wortsman, Maxwell Horton, Carlos Guestrin,
Random Walk Graph Neural Networks
Random Walk Graph Neural Networks This repository is the official implementation of Random Walk Graph Neural Networks. Requirements Code is written in
SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow
SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow, in High Performance Computing (HPC) simulations and workloads.
JittorVis is a deep neural network computational graph visualization library based on Jittor.
JittorVis - Visual understanding of deep learning model.
The `rtdl` library + The official implementation of the paper
The `rtdl` library + The official implementation of the paper "Revisiting Deep Learning Models for Tabular Data"
An intelligent, flexible grammar of machine learning.
An english representation of machine learning. Modify what you want, let us handle the rest. Overview Nylon is a python library that lets you customiz
PyTorch implementation of "ContextNet: Improving Convolutional Neural Networks for Automatic Speech Recognition with Global Context" (INTERSPEECH 2020)
ContextNet ContextNet has CNN-RNN-transducer architecture and features a fully convolutional encoder that incorporates global context information into