5726 Repositories
Python deep-transfer-learning Libraries
Composing methods for ML training efficiency
MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training.
Unofficial Implementation of MLP-Mixer, gMLP, resMLP, Vision Permutator, S2MLPv2, RaftMLP, ConvMLP, ConvMixer in Jittor and PyTorch.
Unofficial Implementation of MLP-Mixer, gMLP, resMLP, Vision Permutator, S2MLPv2, RaftMLP, ConvMLP, ConvMixer in Jittor and PyTorch! Now, Rearrange and Reduce in einops.layers.jittor are support!!
GUI for a Vocal Remover that uses Deep Neural Networks.
GUI for a Vocal Remover that uses Deep Neural Networks.
Multiple style transfer via variational autoencoder
ST-VAE Multiple style transfer via variational autoencoder By Zhi-Song Liu, Vicky Kalogeiton and Marie-Paule Cani This repo only provides simple testi
A style-based Quantum Generative Adversarial Network
Style-qGAN A style based Quantum Generative Adversarial Network (style-qGAN) model for Monte Carlo event generation. Tutorial We have prepared a noteb
SoGCN: Second-Order Graph Convolutional Networks
SoGCN: Second-Order Graph Convolutional Networks This is the authors' implementation of paper "SoGCN: Second-Order Graph Convolutional Networks" in Py
Implementation of "DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration Testing".
DeepOrder Implementation of DeepOrder for the paper "DeepOrder: Deep Learning for Test Case Prioritization in Continuous Integration Testing". Project
Using contrastive learning and OpenAI's CLIP to find good embeddings for images with lossy transformations
Creating Robust Representations from Pre-Trained Image Encoders using Contrastive Learning Sriram Ravula, Georgios Smyrnis This is the code for our pr
novel deep learning research works with PaddlePaddle
Research 发布基于飞桨的前沿研究工作,包括CV、NLP、KG、STDM等领域的顶会论文和比赛冠军模型。 目录 计算机视觉(Computer Vision) 自然语言处理(Natrual Language Processing) 知识图谱(Knowledge Graph) 时空数据挖掘(Spa
DeepMoCap: Deep Optical Motion Capture using multiple Depth Sensors and Retro-reflectors
DeepMoCap: Deep Optical Motion Capture using multiple Depth Sensors and Retro-reflectors By Anargyros Chatzitofis, Dimitris Zarpalas, Stefanos Kollias
Code and data of the EMNLP 2021 paper "Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer"
StyleAttack Code and data of the EMNLP 2021 paper "Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer" Prepare Pois
Semi-supervised Transfer Learning for Image Rain Removal. In CVPR 2019.
Semi-supervised Transfer Learning for Image Rain Removal This package contains the Python implementation of "Semi-supervised Transfer Learning for Ima
Image Super-Resolution by Neural Texture Transfer
SRNTT: Image Super-Resolution by Neural Texture Transfer Tensorflow implementation of the paper Image Super-Resolution by Neural Texture Transfer acce
PyTorch version of the paper 'Enhanced Deep Residual Networks for Single Image Super-Resolution' (CVPRW 2017)
About PyTorch 1.2.0 Now the master branch supports PyTorch 1.2.0 by default. Due to the serious version problem (especially torch.utils.data.dataloade
Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" (NeurIPS'20)
IGNN Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" [paper] [supp] Prepare datasets 1 Download training dataset
Pytorch implementation of the paper: "A Unified Framework for Separating Superimposed Images", in CVPR 2020.
Deep Adversarial Decomposition PDF | Supp | 1min-DemoVideo Pytorch implementation of the paper: "Deep Adversarial Decomposition: A Unified Framework f
Benchmark datasets, data loaders, and evaluators for graph machine learning
Overview The Open Graph Benchmark (OGB) is a collection of benchmark datasets, data loaders, and evaluators for graph machine learning. Datasets cover
official implementation for the paper "Simplifying Graph Convolutional Networks"
Simplifying Graph Convolutional Networks Updates As pointed out by #23, there was a subtle bug in our preprocessing code for the reddit dataset. After
IsoGCN code for ICLR2021
IsoGCN The official implementation of IsoGCN, presented in the ICLR2021 paper Isometric Transformation Invariant and Equivariant Graph Convolutional N
PyTorch implementation of "Simple and Deep Graph Convolutional Networks"
Simple and Deep Graph Convolutional Networks This repository contains a PyTorch implementation of "Simple and Deep Graph Convolutional Networks".(http
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks This repository contains a TensorFlow implementation of "
[ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
When Does Self-Supervision Help Graph Convolutional Networks? PyTorch implementation for When Does Self-Supervision Help Graph Convolutional Networks?
This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Con
Repository for benchmarking graph neural networks
Benchmarking Graph Neural Networks Updates Nov 2, 2020 Project based on DGL 0.4.2. See the relevant dependencies defined in the environment yml files
Tensorflow Repo for "DeepGCNs: Can GCNs Go as Deep as CNNs?"
DeepGCNs: Can GCNs Go as Deep as CNNs? In this work, we present new ways to successfully train very deep GCNs. We borrow concepts from CNNs, mainly re
Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).
Densely Connected Convolutional Networks (DenseNets) This repository contains the code for DenseNet introduced in the following paper Densely Connecte
Deep Residual Networks with 1K Layers
Deep Residual Networks with 1K Layers By Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. Microsoft Research Asia (MSRA). Table of Contents Introduc
A torch.Tensor-like DataFrame library supporting multiple execution runtimes and Arrow as a common memory format
TorchArrow (Warning: Unstable Prototype) This is a prototype library currently under heavy development. It does not currently have stable releases, an
Collection of Docker images for ML/DL and video processing projects
Collection of Docker images for ML/DL and video processing projects. Overview of images Three types of images differ by tag postfix: base: Python with
An implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch
This work has now been superseded by: https://github.com/sniklaus/revisiting-sepconv sepconv-slomo This is a reference implementation of Video Frame I
RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation
RIFE - Real Time Video Interpolation arXiv | YouTube | Colab | Tutorial | Demo Table of Contents Introduction Collection Usage Evaluation Training and
Youtube Downloader is a Graphic User Interface(GUI) that lets users download a Youtube Video or Audio through a URL
Youtube Downloader This Python and Tkinter based GUI allows users to directly download the Best Resolution Videos and Audios from Youtube. Pa-fy Insta
an implementation of Revisiting Adaptive Convolutions for Video Frame Interpolation using PyTorch
revisiting-sepconv This is a reference implementation of Revisiting Adaptive Convolutions for Video Frame Interpolation [1] using PyTorch. Given two f
Bittensor - an open, decentralized, peer-to-peer network that functions as a market system for the development of artificial intelligence
At Bittensor, we are creating an open, decentralized, peer-to-peer network that functions as a market system for the development of artificial intelligence.
Solutions of Reinforcement Learning 2nd Edition
Solutions of Reinforcement Learning, An Introduction
LibreLingo🐢 🌎 📚 a community-owned language-learning platform
LibreLingo's mission is to create a modern language-learning platform that is owned by the community of its users. All software is licensed under AGPLv3, which guarantees the freedom to run, study, share, and modify the software. Course authors are encouraged to release their courses with free licenses.
A JAX implementation of Broaden Your Views for Self-Supervised Video Learning, or BraVe for short.
BraVe This is a JAX implementation of Broaden Your Views for Self-Supervised Video Learning, or BraVe for short. The model provided in this package wa
BLEURT is a metric for Natural Language Generation based on transfer learning.
BLEURT: a Transfer Learning-Based Metric for Natural Language Generation BLEURT is an evaluation metric for Natural Language Generation. It takes a pa
Self-Supervised Speech Pre-training and Representation Learning Toolkit.
What's New Sep 2021: We host a challenge in AAAI workshop: The 2nd Self-supervised Learning for Audio and Speech Processing! See SUPERB official site
UniSpeech - Large Scale Self-Supervised Learning for Speech
UniSpeech The family of UniSpeech: UniSpeech (ICML 2021): Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR UniSpeech-
PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids
PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids The electric grid is a key enabling infrastructure for the a
Code for WSDM 2022 paper, Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation.
DuoRec Code for WSDM 2022 paper, Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation. Usage Download datasets fr
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning Preprocess file of the dataset used in implicit sub-populations: (Demographic groups
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W
Code for the preprint "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"
This is a repository for the paper of "Well-classified Examples are Underestimated in Classification with Deep Neural Networks" The implementation and
Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment"
DSN-IQA Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment" Requirements Python =3.8.0 Pytorch =1.7.1 Usage wit
[SIGGRAPH 2021 Asia] DeepVecFont: Synthesizing High-quality Vector Fonts via Dual-modality Learning
DeepVecFont This is the official Pytorch implementation of the paper: Yizhi Wang and Zhouhui Lian. DeepVecFont: Synthesizing High-quality Vector Fonts
Deep Sea Treasure Environment for Multi-Objective Optimization Research
DeepSeaTreasure Environment Installation In order to get started with this environment, you can install it using the following command: python3 -m pip
Next-Best-View Estimation based on Deep Reinforcement Learning for Active Object Classification
next_best_view_rl Setup Clone the repository: git clone --recurse-submodules ... In 'third_party/zed-ros-wrapper': git checkout devel Install mujoco `
A cross-lingual COVID-19 fake news dataset
CrossFake An English-Chinese COVID-19 fake&real news dataset from the ICDMW 2021 paper below: Cross-lingual COVID-19 Fake News Detection. Jiangshu Du,
Codebase of deep learning models for inferring stability of mRNA molecules
Kaggle OpenVaccine Models Codebase of deep learning models for inferring stability of mRNA molecules, corresponding to the Kaggle Open Vaccine Challen
This is an official pytorch implementation of Fast Fourier Convolution.
Fast Fourier Convolution (FFC) for Image Classification This is the official code of Fast Fourier Convolution for image classification on ImageNet. Ma
Direct design of biquad filter cascades with deep learning by sampling random polynomials.
IIRNet Direct design of biquad filter cascades with deep learning by sampling random polynomials. Usage git clone https://github.com/csteinmetz1/IIRNe
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight)
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight) Abstract Due to the limited and even imbalanced dat
This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEECH" submitted to ICASSP 2022
CPC_DeepCluster This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEEC
Official implementation of "Motif-based Graph Self-Supervised Learning forMolecular Property Prediction"
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction Official Pytorch implementation of NeurIPS'21 paper "Motif-based Graph Se
Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment"
DSN-IQA Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment" Requirements Python =3.8.0 Pytorch =1.7.1 Usage wit
Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection, AAAI 2021.
Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection This repository is an official implementation of the AAAI 2021 paper Co-mi
The easy way to combine mlflow, hydra and optuna into one machine learning pipeline.
mlflow_hydra_optuna_the_easy_way The easy way to combine mlflow, hydra and optuna into one machine learning pipeline. Objective TODO Usage 1. build do
A PyTorch implementation of paper "Learning Shared Semantic Space for Speech-to-Text Translation", ACL (Findings) 2021
Chimera: Learning Shared Semantic Space for Speech-to-Text Translation This is a Pytorch implementation for the "Chimera" paper Learning Shared Semant
African language Speech Recognition - Speech-to-Text
Swahili-Speech-To-Text Table of Contents Swahili-Speech-To-Text Overview Scenario Approach Project Structure data: models: notebooks: scripts tests: l
A collection of learning outcomes data analysis using Python and SQL, from DQLab.
Data Analyst with PYTHON Data Analyst berperan dalam menghasilkan analisa data serta mempresentasikan insight untuk membantu proses pengambilan keputu
An end-to-end regression problem of predicting the price of properties in Bangalore.
Bangalore-House-Price-Prediction An end-to-end regression problem of predicting the price of properties in Bangalore. Deployed in Heroku using Flask.
Python codes for the server and client end that facilitates file transfers. (Using AWS EC2 instance as the server)
Server-and-Client-File-Transfer Python codes for the server and client end that facilitates file transfers. I will be using an AWS EC2 instance as the
RL-driven agent playing tic-tac-toe on starknet against challengers.
tictactoe-on-starknet RL-driven agent playing tic-tac-toe on starknet against challengers. GUI reference: https://pythonguides.com/create-a-game-using
MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training
MosaicML Composer MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training. We aim to ease th
Offline Reinforcement Learning with Implicit Q-Learning
Offline Reinforcement Learning with Implicit Q-Learning This repository contains the official implementation of Offline Reinforcement Learning with Im
ImageNet-CoG is a benchmark for concept generalization. It provides a full evaluation framework for pre-trained visual representations which measure how well they generalize to unseen concepts.
The ImageNet-CoG Benchmark Project Website Paper (arXiv) Code repository for the ImageNet-CoG Benchmark introduced in the paper "Concept Generalizatio
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W
Official Repo for ICCV2021 Paper: Learning to Regress Bodies from Images using Differentiable Semantic Rendering
[ICCV2021] Learning to Regress Bodies from Images using Differentiable Semantic Rendering Getting Started DSR has been implemented and tested on Ubunt
Learning from Synthetic Data with Fine-grained Attributes for Person Re-Identification
Less is More: Learning from Synthetic Data with Fine-grained Attributes for Person Re-Identification Suncheng Xiang Shanghai Jiao Tong University Over
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning This repository is the official implementation of CARE.
Disease Informed Neural Networks (DINNs) — neural networks capable of learning how diseases spread, forecasting their progression, and finding their unique parameters (e.g. death rate).
DINN We introduce Disease Informed Neural Networks (DINNs) — neural networks capable of learning how diseases spread, forecasting their progression, a
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight)
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight) Abstract Due to the limited and even imbalanced dat
BuildingNet: Learning to Label 3D Buildings
BuildingNet This is the implementation of the BuildingNet architecture described in this paper: Paper: BuildingNet: Learning to Label 3D Buildings Arx
TCube generates rich and fluent narratives that describes the characteristics, trends, and anomalies of any time-series data (domain-agnostic) using the transfer learning capabilities of PLMs.
TCube: Domain-Agnostic Neural Time series Narration This repository contains the code for the paper: "TCube: Domain-Agnostic Neural Time series Narrat
Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations
Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations This repo contains official code for the NeurIPS 2021 paper Imi
Safe Model-Based Reinforcement Learning using Robust Control Barrier Functions
README Repository containing the code for the paper "Safe Model-Based Reinforcement Learning using Robust Control Barrier Functions". Specifically, an
Instance-based label smoothing for improving deep neural networks generalization and calibration
Instance-based Label Smoothing for Neural Networks Pytorch Implementation of the algorithm. This repository includes a new proposed method for instanc
DP-CL(Continual Learning with Differential Privacy)
DP-CL(Continual Learning with Differential Privacy) This is the official implementation of the Continual Learning with Differential Privacy. If you us
Simple (but Strong) Baselines for POMDPs
Recurrent Model-Free RL is a Strong Baseline for Many POMDPs Welcome to the POMDP world! This repo provides some simple baselines for POMDPs, specific
Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database.
MIMIC-III Benchmarks Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database. Currently, the benchmark data
Deep learning models for classification of 15 common weeds in the southern U.S. cotton production systems.
CottonWeeds Deep learning models for classification of 15 common weeds in the southern U.S. cotton production systems. requirements pytorch torchsumma
Noise supression using deep filtering
DeepFilterNet A Low Complexity Speech Enhancement Framework for Full-Band Audio (48kHz) based on Deep Filtering. libDF contains Rust code used for dat
Offline Reinforcement Learning with Implicit Q-Learning
Offline Reinforcement Learning with Implicit Q-Learning This repository contains the official implementation of Offline Reinforcement Learning with Im
University of Rochester 2021 Summer REU focusing on music sentiment transfer using CycleGAN
Music-Sentiment-Transfer University of Rochester 2021 Summer REU focusing on music sentiment transfer using CycleGAN Poster: Music Sentiment Transfer
Deep Federated Learning for Autonomous Driving
FADNet: Deep Federated Learning for Autonomous Driving Abstract Autonomous driving is an active research topic in both academia and industry. However,
Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.
3D Infomax improves GNNs for Molecular Property Prediction Video | Paper We pre-train GNNs to understand the geometry of molecules given only their 2D
The Official PyTorch Implementation of DiscoBox.
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision Paper | Project page | Demo (Youtube) | Demo (Bilib
Code and project page for ICCV 2021 paper "DisUnknown: Distilling Unknown Factors for Disentanglement Learning"
DisUnknown: Distilling Unknown Factors for Disentanglement Learning See introduction on our project page Requirements PyTorch = 1.8.0 torch.linalg.ei
PyTorch implementation of our CVPR2021 (oral) paper "Prototype Augmentation and Self-Supervision for Incremental Learning"
PASS - Official PyTorch Implementation [CVPR2021 Oral] Prototype Augmentation and Self-Supervision for Incremental Learning Fei Zhu, Xu-Yao Zhang, Chu
[ICCV 2021 Oral] Deep Evidential Action Recognition
DEAR (Deep Evidential Action Recognition) Project | Paper & Supp Wentao Bao, Qi Yu, Yu Kong International Conference on Computer Vision (ICCV Oral), 2
i3DMM: Deep Implicit 3D Morphable Model of Human Heads
i3DMM: Deep Implicit 3D Morphable Model of Human Heads CVPR 2021 (Oral) Arxiv | Poject Page This project is the official implementation our work, i3DM
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning
BasicRL: easy and fundamental codes for deep reinforcement learning。It is an improvement on rainbow-is-all-you-need and OpenAI Spinning Up.
BasicRL: easy and fundamental codes for deep reinforcement learning BasicRL is an improvement on rainbow-is-all-you-need and OpenAI Spinning Up. It is
A Low Complexity Speech Enhancement Framework for Full-Band Audio (48kHz) based on Deep Filtering.
DeepFilterNet A Low Complexity Speech Enhancement Framework for Full-Band Audio (48kHz) based on Deep Filtering. libDF contains Rust code used for dat
The Few-Shot Bot: Prompt-Based Learning for Dialogue Systems
Few-Shot Bot: Prompt-Based Learning for Dialogue Systems This repository includes the dataset, experiments results, and code for the paper: Few-Shot B
Reinforcement Learning for the Blackjack
Reinforcement Learning for Blackjack Author: ZHA Mengyue Math Department of HKUST Problem Statement We study playing Blackjack by reinforcement learni
Audio-Visual Generalized Few-Shot Learning with Prototype-Based Co-Adaptation
Audio-Visual Generalized Few-Shot Learning with Prototype-Based Co-Adaptation The code repository for "Audio-Visual Generalized Few-Shot Learning with
Jarvis Project is a basic virtual assistant that uses TensorFlow for learning.
Jarvis_proyect Jarvis Project is a basic virtual assistant that uses TensorFlow for learning. Latest version 0.1 Features: Good morning protocol Tell