5987 Repositories
Python graph-deep-learning Libraries
Malaya-Speech is a Speech-Toolkit library for bahasa Malaysia, powered by Deep Learning Tensorflow.
Malaya-Speech is a Speech-Toolkit library for bahasa Malaysia, powered by Deep Learning Tensorflow. Documentation Proper documentation is available at
Code for CodeT5: a new code-aware pre-trained encoder-decoder model.
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation This is the official PyTorch implementation
Edge-Augmented Graph Transformer
Edge-augmented Graph Transformer Introduction This is the official implementation of the Edge-augmented Graph Transformer (EGT) as described in https:
Repo for Enhanced Seq2Seq Autoencoder via Contrastive Learning for Abstractive Text Summarization
ESACL: Enhanced Seq2Seq Autoencoder via Contrastive Learning for AbstractiveText Summarization This repo is for our paper "Enhanced Seq2Seq Autoencode
The code for the Subformer, from the EMNLP 2021 Findings paper: "Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers", by Machel Reid, Edison Marrese-Taylor, and Yutaka Matsuo
Subformer This repository contains the code for the Subformer. To help overcome this we propose the Subformer, allowing us to retain performance while
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models
Large-scale pretraining for dialogue
A State-of-the-Art Large-scale Pretrained Response Generation Model (DialoGPT) This repository contains the source code and trained model for a large-
Sinkhorn Transformer - Practical implementation of Sparse Sinkhorn Attention
Sinkhorn Transformer This is a reproduction of the work outlined in Sparse Sinkhorn Attention, with additional enhancements. It includes a parameteriz
DeLighT: Very Deep and Light-Weight Transformers
DeLighT: Very Deep and Light-weight Transformers This repository contains the source code of our work on building efficient sequence models: DeFINE (I
Fully featured implementation of Routing Transformer
Routing Transformer A fully featured implementation of Routing Transformer. The paper proposes using k-means to route similar queries / keys into the
DeBERTa: Decoding-enhanced BERT with Disentangled Attention
DeBERTa: Decoding-enhanced BERT with Disentangled Attention This repository is the official implementation of DeBERTa: Decoding-enhanced BERT with Dis
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
ELECTRA Introduction ELECTRA is a method for self-supervised language representation learning. It can be used to pre-train transformer networks using
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
ALBERT ***************New March 28, 2020 *************** Add a colab tutorial to run fine-tuning for GLUE datasets. ***************New January 7, 2020
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
Tensor2Tensor Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and ac
This is the repository for the NeurIPS-21 paper [Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels].
CGPN This is the repository for the NeurIPS-21 paper [Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels]. Req
Infrastructure template and Jupyter notebooks for running RoseTTAFold on AWS Batch.
AWS RoseTTAFold Infrastructure template and Jupyter notebooks for running RoseTTAFold on AWS Batch. Overview Proteins are large biomolecules that play
This project impelemented for midterm of the Machine Learning #Zoomcamp #Alexey Grigorev
MLProject_01 This project impelemented for midterm of the Machine Learning #Zoomcamp #Alexey Grigorev Context Dataset English question data set file F
A curated list of long-tailed recognition resources.
Awesome Long-tailed Recognition A curated list of long-tailed recognition and related resources. Please feel free to pull requests or open an issue to
Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"
Class-balanced-loss-pytorch Pytorch implementation of the paper Class-Balanced Loss Based on Effective Number of Samples presented at CVPR'19. Yin Cui
Pytorch codes for Feature Transfer Learning for Face Recognition with Under-Represented Data
FTLNet_Pytorch Pytorch codes for Feature Transfer Learning for Face Recognition with Under-Represented Data 1. Introduction This repo is an unofficial
Reimplementation of NeurIPS'19: "Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting" by Shu et al.
[Re] Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting Reimplementation of NeurIPS'19: "Meta-Weight-Net: Learning an Explicit Mapping
Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning. CVPR 2018
Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning Tensorflow code and models for the paper: Large Scale Fine-Grained Categ
Code for paper "Learning to Reweight Examples for Robust Deep Learning"
learning-to-reweight-examples Code for paper Learning to Reweight Examples for Robust Deep Learning. [arxiv] Environment We tested the code on tensorf
PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning
Learning to Reweight Examples for Robust Deep Learning Unofficial PyTorch implementation of Learning to Reweight Examples for Robust Deep Learning. Th
A Pytorch reproduction of Range Loss, which is proposed in paper 《Range Loss for Deep Face Recognition with Long-Tailed Training Data》
RangeLoss Pytorch This is a Pytorch reproduction of Range Loss, which is proposed in paper 《Range Loss for Deep Face Recognition with Long-Tailed Trai
Adjust Decision Boundary for Class Imbalanced Learning
Adjusting Decision Boundary for Class Imbalanced Learning This repository is the official PyTorch implementation of WVN-RS, introduced in Adjusting De
[WACV21] Code for our paper: Samuel, Atzmon and Chechik, "From Generalized zero-shot learning to long-tail with class descriptors"
DRAGON: From Generalized zero-shot learning to long-tail with class descriptors Paper Project Website Video Overview DRAGON learns to correct the bias
Deep learning for Engineers - Physics Informed Deep Learning
SciANN: Neural Networks for Scientific Computations SciANN is a Keras wrapper for scientific computations and physics-informed deep learning. New to S
Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing
Notice: Support for Python 3.6 will be dropped in v.0.2.1, please plan accordingly! Efficient and Scalable Physics-Informed Deep Learning Collocation-
PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks
PyDEns PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks. With PyDEns one can solve PD
Physics-Informed Neural Networks (PINN) and Deep BSDE Solvers of Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
NeuralPDE NeuralPDE.jl is a solver package which consists of neural network solvers for partial differential equations using scientific machine learni
Learn the Deep Learning for Computer Vision in three steps: theory from base to SotA, code in PyTorch, and space-repetition with Anki
DeepCourse: Deep Learning for Computer Vision arthurdouillard.com/deepcourse/ This is a course I'm giving to the French engineering school EPITA each
Continual World is a benchmark for continual reinforcement learning
Continual World Continual World is a benchmark for continual reinforcement learning. It contains realistic robotic tasks which come from MetaWorld. Th
Deep Learning Theory
Deep Learning Theory 整理了一些深度学习的理论相关内容,持续更新。 Overview Recent advances in deep learning theory 总结了目前深度学习理论研究的六个方向的一些结果,概述型,没做深入探讨(2021)。 1.1 complexity
PyContinual (An Easy and Extendible Framework for Continual Learning)
PyContinual (An Easy and Extendible Framework for Continual Learning) Easy to Use You can sumply change the baseline, backbone and task, and then read
The implementation of Learning Instance and Task-Aware Dynamic Kernels for Few Shot Learning
INSTA: Learning Instance and Task-Aware Dynamic Kernels for Few Shot Learning This repository provides the implementation and demo of Learning Instanc
Implementation of Research Paper "Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation"
Zero-DCE and Zero-DCE++(Lite architechture for Mobile and edge Devices) Papers Abstract The paper presents a novel method, Zero-Reference Deep Curve E
People Interaction Graph
Gihan Jayatilaka*, Jameel Hassan*, Suren Sritharan*, Janith Senananayaka, Harshana Weligampola, et. al., 2021. Holistic Interpretation of Public Scenes Using Computer Vision and Temporal Graphs to Identify Social Distancing Violations. arXiv preprint.
Conjugated Discrete Distributions for Distributional Reinforcement Learning (C2D)
Conjugated Discrete Distributions for Distributional Reinforcement Learning (C2D) Code & Data Appendix for Conjugated Discrete Distributions for Distr
Decentralised graph database management system
Decentralised graph database management system To get started clone the repo, and run the command below. python3 database.py Now, create a new termina
MARS: Learning Modality-Agnostic Representation for Scalable Cross-media Retrieva
Introduction This is the source code of our TCSVT 2021 paper "MARS: Learning Modality-Agnostic Representation for Scalable Cross-media Retrieval". Ple
Manipulation OpenAI Gym environments to simulate robots at the STARS lab
Manipulator Learning This repository contains a set of manipulation environments that are compatible with OpenAI Gym and simulated in pybullet. In par
Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning Source Code
Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning Source Code
In generative deep geometry learning, we often get many obj files remain to be rendered
a python prompt cli script for blender batch render In deep generative geometry learning, we always get many .obj files to be rendered. Our rendered i
Quickly visualize docker networks with graphviz.
Docker Network Graph Visualize the relationship between Docker networks and containers as a neat graphviz graph. Example Usage usage: docker-net-graph
Text Classification in Turkish Texts with Bert
You can watch the details of the project on my youtube channel Project Interface Project Second Interface Goal= Correctly guessing the classification
A foreign language learning aid using a neural network to predict probability of translating foreign words
Langy Langy is a reading-focused foreign language learning aid orientated towards young children. Reading is an activity that every child knows. It is
The projects lets you extract glossary words and their definitions from a given piece of text automatically using NLP techniques
Unsupervised technique to Glossary and Definition Extraction Code Files GPT2-DefinitionModel.ipynb - GPT-2 model for definition generation. Data_Gener
Predict an emoji that is associated with a text
Sentiment Analysis Sentiment analysis in computational linguistics is a general term for techniques that quantify sentiment or mood in a text. Can you
This repository is the official implementation of the Hybrid Self-Attention NEAT algorithm.
This repository is the official implementation of the Hybrid Self-Attention NEAT algorithm. It contains the code to reproduce the results presented in the original paper: https://arxiv.org/abs/2112.03670
Hierarchical Clustering: O(1)-Approximation for Well-Clustered Graphs
Hierarchical Clustering: O(1)-Approximation for Well-Clustered Graphs This repository contains code to accompany the paper "Hierarchical Clustering: O
Telegram chatbot created with deep learning model (LSTM) and telebot library.
Telegram chatbot Telegram chatbot created with deep learning model (LSTM) and telebot library. Description This program will allow you to create very
A PaddlePaddle version of Neural Renderer, refer to its PyTorch version
Neural 3D Mesh Renderer in PadddlePaddle A PaddlePaddle version of Neural Renderer, refer to its PyTorch version Install Run: pip install neural-rende
Robbing the FED: Directly Obtaining Private Data in Federated Learning with Modified Models
Robbing the FED: Directly Obtaining Private Data in Federated Learning with Modified Models This repo contains a barebones implementation for the atta
An official source code for paper Deep Graph Clustering via Dual Correlation Reduction, accepted by AAAI 2022
Dual Correlation Reduction Network An official source code for paper Deep Graph Clustering via Dual Correlation Reduction, accepted by AAAI 2022. Any
Official Pytorch implementation for Deep Contextual Video Compression, NeurIPS 2021
Introduction Official Pytorch implementation for Deep Contextual Video Compression, NeurIPS 2021 Prerequisites Python 3.8 and conda, get Conda CUDA 11
Joint learning of images and text via maximization of mutual information
mutual_info_img_txt Joint learning of images and text via maximization of mutual information. This repository incorporates the algorithms presented in
SPEAR: Semi suPErvised dAta progRamming
Semi-Supervised Data Programming for Data Efficient Machine Learning SPEAR is a library for data programming with semi-supervision. The package implem
PantheonRL is a package for training and testing multi-agent reinforcement learning environments.
PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.
Library to enable Bayesian active learning in your research or labeling work.
Bayesian Active Learning (BaaL) BaaL is an active learning library developed at ElementAI. This repository contains techniques and reusable components
Experiments on continual learning from a stream of pretrained models.
Ex-model CL Ex-model continual learning is a setting where a stream of experts (i.e. model's parameters) is available and a CL model learns from them
[AAAI 2022] Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification
Sparse Structure Learning via Graph Neural Networks for inductive document classification Make graph dataset create co-occurrence graph for datasets.
Official code repository for Continual Learning In Environments With Polynomial Mixing Times
Official code for Continual Learning In Environments With Polynomial Mixing Times Continual Learning in Environments with Polynomial Mixing Times This
DeepDiffusion: Unsupervised Learning of Retrieval-adapted Representations via Diffusion-based Ranking on Latent Feature Manifold
DeepDiffusion Introduction This repository provides the code of the DeepDiffusion algorithm for unsupervised learning of retrieval-adapted representat
Official code base for the poster "On the use of Cortical Magnification and Saccades as Biological Proxies for Data Augmentation" published in NeurIPS 2021 Workshop (SVRHM)
Self-Supervised Learning (SimCLR) with Biological Plausible Image Augmentations Official code base for the poster "On the use of Cortical Magnificatio
ALIbaba's Collection of Encoder-decoders from MinD (Machine IntelligeNce of Damo) Lab
AliceMind AliceMind: ALIbaba's Collection of Encoder-decoders from MinD (Machine IntelligeNce of Damo) Lab This repository provides pre-trained encode
A high-performance distributed deep learning system targeting large-scale and automated distributed training.
HETU Documentation | Examples Hetu is a high-performance distributed deep learning system targeting trillions of parameters DL model training, develop
A computational block to solve entity alignment over textual attributes in a knowledge graph creation pipeline.
How to apply? Create your config.ini file following the example provided in config.ini Choose one of the options below to run: Run with Python3 pip in
Sleep staging from ECG, assisted with EEG
Sleep_Staging_Knowledge Distillation This codebase implements knowledge distillation approach for ECG based sleep staging assisted by EEG based sleep
Type4Py: Deep Similarity Learning-Based Type Inference for Python
Type4Py: Deep Similarity Learning-Based Type Inference for Python This repository contains the implementation of Type4Py and instructions for re-produ
A GitHub action that suggests type annotations for Python using machine learning.
Typilus: Suggest Python Type Annotations A GitHub action that suggests type annotations for Python using machine learning. This action makes suggestio
AI4Good project for detecting waste in the environment
Detect waste AI4Good project for detecting waste in environment. www.detectwaste.ml. Our latest results were published in Waste Management journal in
Official implementation of the paper "Lightweight Deep CNN for Natural Image Matting via Similarity Preserving Knowledge Distillation"
Lightweight-Deep-CNN-for-Natural-Image-Matting-via-Similarity-Preserving-Knowledge-Distillation Introduction Accepted at IEEE Signal Processing Letter
A powerful framework for decentralized federated learning with user-defined communication topology
Scatterbrained Decentralized Federated Learning Scatterbrained makes it easy to build federated learning systems. In addition to traditional federated
Coursera learning course Python the basics. Programming exercises and tasks
HSE_Python_the_basics Welcome to BAsics programming Python! You’re joining thousands of learners currently enrolled in the course. I'm excited to have
Component for deep integration LedFx from Home Assistant.
LedFX for Home Assistant Component for deep integration LedFx from Home Assistant. Table of Contents FAQ Install Config Performance FAQ Q. What versio
Learning Lightweight Low-Light Enhancement Network using Pseudo Well-Exposed Images
Learning Lightweight Low-Light Enhancement Network using Pseudo Well-Exposed Images This repository contains the implementation of the following paper
The source code of the paper "SHGNN: Structure-Aware Heterogeneous Graph Neural Network"
SHGNN: Structure-Aware Heterogeneous Graph Neural Network The source code and dataset of the paper: SHGNN: Structure-Aware Heterogeneous Graph Neural
This is a graphql api build using ariadne python that serves a graphql-endpoint at port 3002 to perform language translation and identification using deep learning in python pytorch.
Language Translation and Identification this machine/deep learning api that will be served as a graphql-api using ariadne, to perform the following ta
Implementation of parameterized soft-exponential activation function.
Soft-Exponential-Activation-Function: Implementation of parameterized soft-exponential activation function. In this implementation, the parameters are
Self-Supervised Learning
Self-Supervised Learning Features self_supervised offers features like modular framework support for multi-gpu training using PyTorch Lightning easy t
MLReef is an open source ML-Ops platform that helps you collaborate, reproduce and share your Machine Learning work with thousands of other users.
The collaboration platform for Machine Learning MLReef is an open source ML-Ops platform that helps you collaborate, reproduce and share your Machine
A python interface for training Reinforcement Learning bots to battle on pokemon showdown
The pokemon showdown Python environment A Python interface to create battling pokemon agents. poke-env offers an easy-to-use interface for creating ru
A lightweight, pure-Python mobile robot simulator designed for experiments in Artificial Intelligence (AI) and Machine Learning, especially for Jupyter Notebooks
aitk.robots A lightweight Python robot simulator for JupyterLab, Notebooks, and other Python environments. Goals A lightweight mobile robotics simulat
Predicting Baseball Metric Clusters: Clustering Application in Python Using scikit-learn
Clustering Clustering Application in Python Using scikit-learn This repository contains the prediction of baseball metric clusters using MLB Statcast
PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
PyGAD: Genetic Algorithm in Python PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine lear
Official implementation of the paper "Backdoor Attacks on Self-Supervised Learning".
SSL-Backdoor Abstract Large-scale unlabeled data has allowed recent progress in self-supervised learning methods that learn rich visual representation
NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.
NCVX (NonConVeX): A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning.
Learning with Subset Stacking
Learning with Subset Stacking (LESS) LESS is a new supervised learning algorithm that is based on training many local estimators on subsets of a given
Implementation of "Semi-supervised Domain Adaptive Structure Learning"
Semi-supervised Domain Adaptive Structure Learning - ASDA This repo contains the source code and dataset for our ASDA paper. Illustration of the propo
These are the materials for the paper "Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations"
Few-shot-NLEs These are the materials for the paper "Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations". You can find the smal
Supervised & unsupervised machine-learning techniques are applied to the database of weighted P4s which admit Calabi-Yau hypersurfaces.
Weighted Projective Spaces ML Description: The database of 5-vectors describing 4d weighted projective spaces which admit Calabi-Yau hypersurfaces are
Twin-deep neural network for semi-supervised learning of materials properties
Deep Semi-Supervised Teacher-Student Material Synthesizability Prediction Citation: Semi-supervised teacher-student deep neural network for materials
FinRL-Meta: A Universe for Data-Driven Financial Reinforcement Learning. 🔥
FinRL-Meta: A Universe of Market Environments. FinRL-Meta is a universe of market environments for data-driven financial reinforcement learning. Users
Semantic graph parser based on Categorial grammars
Lambekseq "Everyone who failed Greek or Latin hates it." This package is for proving theorems in Categorial grammars (CG) and constructing semantic gr
Centroid-UNet is deep neural network model to detect centroids from satellite images.
Centroid UNet - Locating Object Centroids in Aerial/Serial Images Introduction Centroid-UNet is deep neural network model to detect centroids from Aer
Semantically Contrastive Learning for Low-light Image Enhancement
Semantically Contrastive Learning for Low-light Image Enhancement Here, we propose an effective semantically contrastive learning paradigm for Low-lig
📖 Deep Attentional Guided Image Filtering
📖 Deep Attentional Guided Image Filtering [Paper] Zhiwei Zhong, Xianming Liu, Junjun Jiang, Debin Zhao ,Xiangyang Ji Harbin Institute of Technology,
Hypernetwork-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels
Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels The implementation of Hypernet-Ensemble Le
MinkLoc3D-SI: 3D LiDAR place recognition with sparse convolutions,spherical coordinates, and intensity
MinkLoc3D-SI: 3D LiDAR place recognition with sparse convolutions,spherical coordinates, and intensity Introduction The 3D LiDAR place recognition aim