5334 Repositories
Python online-continual-learning Libraries
PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation
StyleSpeech - PyTorch Implementation PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation. Status (2021.06.09
Deep Learning Package based on TensorFlow
White-Box-Layer is a Python module for deep learning built on top of TensorFlow and is distributed under the MIT license. The project was started in M
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning
We challenge a common assumption underlying most supervised deep learning: that a model makes a prediction depending only on its parameters and the features of a single input. To this end, we introduce a general-purpose deep learning architecture that takes as input the entire dataset instead of processing one datapoint at a time.
Codebase for the Summary Loop paper at ACL2020
Summary Loop This repository contains the code for ACL2020 paper: The Summary Loop: Learning to Write Abstractive Summaries Without Examples. Training
Pytorch implementation of MaskFlownet
MaskFlownet-Pytorch Unofficial PyTorch implementation of MaskFlownet (https://github.com/microsoft/MaskFlownet). Tested with: PyTorch 1.5.0 CUDA 10.1
This code reproduces the results of the paper, "Measuring Data Leakage in Machine-Learning Models with Fisher Information"
Fisher Information Loss This repository contains code that can be used to reproduce the experimental results presented in the paper: Awni Hannun, Chua
Benchmarks for semi-supervised domain generalization.
Semi-Supervised Domain Generalization This code is the official implementation of the following paper: Semi-Supervised Domain Generalization with Stoc
[CVPR'21] DeepSurfels: Learning Online Appearance Fusion
DeepSurfels: Learning Online Appearance Fusion Paper | Video | Project Page This is the official implementation of the CVPR 2021 submission DeepSurfel
"SOLQ: Segmenting Objects by Learning Queries", SOLQ is an end-to-end instance segmentation framework with Transformer.
SOLQ: Segmenting Objects by Learning Queries This repository is an official implementation of the paper SOLQ: Segmenting Objects by Learning Queries.
Official PyTorch implementation of "Adversarial Reciprocal Points Learning for Open Set Recognition"
Adversarial Reciprocal Points Learning for Open Set Recognition Official PyTorch implementation of "Adversarial Reciprocal Points Learning for Open Se
DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification
DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification Created by Yongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie Zhou, Ch
DeepLM: Large-scale Nonlinear Least Squares on Deep Learning Frameworks using Stochastic Domain Decomposition (CVPR 2021)
DeepLM DeepLM: Large-scale Nonlinear Least Squares on Deep Learning Frameworks using Stochastic Domain Decomposition (CVPR 2021) Run Please install th
[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
Delving into Deep Imbalanced Regression This repository contains the implementation code for paper: Delving into Deep Imbalanced Regression Yuzhe Yang
Implementation of Online Label Smoothing in PyTorch
Online Label Smoothing Pytorch implementation of Online Label Smoothing (OLS) presented in Delving Deep into Label Smoothing. Introduction As the abst
This is an implementation for the CVPR2020 paper "Learning Invariant Representation for Unsupervised Image Restoration"
Learning Invariant Representation for Unsupervised Image Restoration (CVPR 2020) Introduction This is an implementation for the paper "Learning Invari
Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments
Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments Paper: arXiv (ICRA 2021) Video : https://youtu.be/CC
Code for our paper "SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization", ACL 2021
SimCLS Code for our paper: "SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization", ACL 2021 1. How to Install Requirements
[CVPR 2021] "The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models" Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Michael Carbin, Zhangyang Wang
The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models Codes for this paper The Lottery Tickets Hypo
Implemented page rank program
Page Rank Implemented page rank program based on fact that a website is more important if it is linked to by other important websites using recursive
Artificial Intelligence playing minesweeper 🤖
AI playing Minesweeper ✨ Minesweeper is a single-player puzzle video game. The objective of the game is to clear a rectangular board containing hidden
The implementation of PEMP in paper "Prior-Enhanced Few-Shot Segmentation with Meta-Prototypes"
Prior-Enhanced network with Meta-Prototypes (PEMP) This is the PyTorch implementation of PEMP. Overview of PEMP Meta-Prototypes & Adaptive Prototypes
Paddle implementation for "Highly Efficient Knowledge Graph Embedding Learning with Closed-Form Orthogonal Procrustes Analysis" (NAACL 2021)
ProcrustEs-KGE Paddle implementation for Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes Analysis 🙈 A more detailed re
A powerful password generator utility which utilizes the slot technique to generate strong passwords of required length having combinations of lower and upper characters, digits and symbols.
Bitpass Password Generator Installation Make sure Python 3+ is installed
Using context-free grammar formalism to parse English sentences to determine their structure to help computer to better understand the meaning of the sentence.
Sentance Parser Executing the Program Make sure Python 3.6+ is installed. Install requirements $ pip install requirements.txt Run the program:
Tutorial on active learning with the Nvidia Transfer Learning Toolkit (TLT).
Active Learning with the Nvidia TLT Tutorial on active learning with the Nvidia Transfer Learning Toolkit (TLT). In this tutorial, we will show you ho
Code for our ACL 2021 (Findings) Paper - Fingerprinting Fine-tuned Language Models in the wild .
🌳 Fingerprinting Fine-tuned Language Models in the wild This is the code and dataset for our ACL 2021 (Findings) Paper - Fingerprinting Fine-tuned La
FEDn is an open-source, modular and ML-framework agnostic framework for Federated Machine Learning
FEDn is an open-source, modular and ML-framework agnostic framework for Federated Machine Learning (FedML) developed and maintained by Scaleout Systems. FEDn enables highly scalable cross-silo and cross-device use-cases over FEDn networks.
Public implementation of "Learning from Suboptimal Demonstration via Self-Supervised Reward Regression" from CoRL'21
Self-Supervised Reward Regression (SSRR) Codebase for CoRL 2021 paper "Learning from Suboptimal Demonstration via Self-Supervised Reward Regression "
PyTorch Code of "Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics"
Memory In Memory Networks It is based on the paper Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spati
Rubik's cube assistant on Flask webapp
webcube Rubik's cube assistant on Flask webapp. This webapp accepts the six faces of your cube and gives you the voice instructions as a response. Req
Deep learning-based approach to discovering Granger causality networks in multivariate time series
Granger causality discovery for neural networks.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Codes for ACL-IJCNLP 2021 Paper "Zero-shot Fact Verification by Claim Generation"
Zero-shot-Fact-Verification-by-Claim-Generation This repository contains code and models for the paper: Zero-shot Fact Verification by Claim Generatio
Repository for the COLING 2020 paper "Explainable Automated Fact-Checking: A Survey."
Explainable Fact Checking: A Survey This repository and the accompanying webpage contain resources for the paper "Explainable Fact Checking: A Survey"
Disagreement-Regularized Imitation Learning
Due to a normalization bug the expert trajectories have lower performance than the rl_baseline_zoo reported experts. Please see the following link in
This is the research repository for Vid2Doppler: Synthesizing Doppler Radar Data from Videos for Training Privacy-Preserving Activity Recognition.
Vid2Doppler: Synthesizing Doppler Radar Data from Videos for Training Privacy-Preserving Activity Recognition This is the research repository for Vid2
Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.
Decision Transformer Lili Chen*, Kevin Lu*, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas†, and Igor M
This is the repo for Uncertainty Quantification 360 Toolkit.
UQ360 The Uncertainty Quantification 360 (UQ360) toolkit is an open-source Python package that provides a diverse set of algorithms to quantify uncert
[CVPR 2021] Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision
TorchSemiSeg [CVPR 2021] Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision by Xiaokang Chen1, Yuhui Yuan2, Gang Zeng1, Jingdong Wang
PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)
PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)
HyperLib: Deep learning in the Hyperbolic space
HyperLib: Deep learning in the Hyperbolic space Background This library implements common Neural Network components in the hypberbolic space (using th
SparseML is a libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models
SparseML is a toolkit that includes APIs, CLIs, scripts and libraries that apply state-of-the-art sparsification algorithms such as pruning and quantization to any neural network. General, recipe-driven approaches built around these algorithms enable the simplification of creating faster and smaller models for the ML performance community at large.
🔬 A curated list of awesome machine learning strategies & tools in financial market.
🔬 A curated list of awesome machine learning strategies & tools in financial market.
PyTorch implementation of: Michieli U. and Zanuttigh P., "Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations", CVPR 2021.
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations This is the official PyTorch implementation
Exploring Visual Engagement Signals for Representation Learning
Exploring Visual Engagement Signals for Representation Learning Menglin Jia, Zuxuan Wu, Austin Reiter, Claire Cardie, Serge Belongie and Ser-Nam Lim C
Code reproduce for paper "Vehicle Re-identification with Viewpoint-aware Metric Learning"
VANET Code reproduce for paper "Vehicle Re-identification with Viewpoint-aware Metric Learning" Introduction This is the implementation of article VAN
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
Implementation of ProteinBERT in Pytorch
ProteinBERT - Pytorch (wip) Implementation of ProteinBERT in Pytorch. Original Repository Install $ pip install protein-bert-pytorch Usage import torc
Framework for joint representation learning, evaluation through multimodal registration and comparison with image translation based approaches
CoMIR: Contrastive Multimodal Image Representation for Registration Framework 🖼 Registration of images in different modalities with Deep Learning 🤖
Official code for "Mean Shift for Self-Supervised Learning"
MSF Official code for "Mean Shift for Self-Supervised Learning" Requirements Python = 3.7.6 PyTorch = 1.4 torchvision = 0.5.0 faiss-gpu = 1.6.1 In
Registration Loss Learning for Deep Probabilistic Point Set Registration
RLLReg This repository contains a Pytorch implementation of the point set registration method RLLReg. Details about the method can be found in the 3DV
chen2020iros: Learning an Overlap-based Observation Model for 3D LiDAR Localization.
Overlap-based 3D LiDAR Monte Carlo Localization This repo contains the code for our IROS2020 paper: Learning an Overlap-based Observation Model for 3D
Official code repository of the paper Learning Associative Inference Using Fast Weight Memory by Schlag et al.
Learning Associative Inference Using Fast Weight Memory This repository contains the offical code for the paper Learning Associative Inference Using F
(AAAI2020)Grapy-ML: Graph Pyramid Mutual Learning for Cross-dataset Human Parsing
Grapy-ML: Graph Pyramid Mutual Learning for Cross-dataset Human Parsing This repository contains pytorch source code for AAAI2020 oral paper: Grapy-ML
Pytorch code for "State-only Imitation with Transition Dynamics Mismatch" (ICLR 2020)
This repo contains code for our paper State-only Imitation with Transition Dynamics Mismatch published at ICLR 2020. The code heavily uses the RL mach
Repository for scripts and notebooks from the book: Programming PyTorch for Deep Learning
Repository for scripts and notebooks from the book: Programming PyTorch for Deep Learning
AI and Machine Learning workflows on Anthos Bare Metal.
Hybrid and Sovereign AI on Anthos Bare Metal Table of Contents Overview Terraform as IaC Substrate ABM Cluster on GCE using Terraform TensorFlow ResNe
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
AndroidEnv is a Python library that exposes an Android device as a Reinforcement Learning (RL) environment.
AndroidEnv is a Python library that exposes an Android device as a Reinforcement Learning (RL) environment.
A New, Interactive Approach to Learning Python
This is the repository for The Python Workshop, published by Packt. It contains all the supporting project files necessary to work through the course from start to finish.
Implementation of ProteinBERT in Pytorch
ProteinBERT - Pytorch (wip) Implementation of ProteinBERT in Pytorch. Original Repository Install $ pip install protein-bert-pytorch Usage import torc
A single Python file with some tools for visualizing machine learning in the terminal.
Machine Learning Visualization Tools A single Python file with some tools for visualizing machine learning in the terminal. This demo is composed of t
This is an official implementation of CvT: Introducing Convolutions to Vision Transformers.
Introduction This is an official implementation of CvT: Introducing Convolutions to Vision Transformers. We present a new architecture, named Convolut
AutoPentest-DRL: Automated Penetration Testing Using Deep Reinforcement Learning
AutoPentest-DRL: Automated Penetration Testing Using Deep Reinforcement Learning AutoPentest-DRL is an automated penetration testing framework based o
Official PyTorch implementation for "Mixed supervision for surface-defect detection: from weakly to fully supervised learning"
Mixed supervision for surface-defect detection: from weakly to fully supervised learning [Computers in Industry 2021] Official PyTorch implementation
FluxTraining.jl gives you an endlessly extensible training loop for deep learning
A flexible neural net training library inspired by fast.ai
DIRL: Domain-Invariant Representation Learning
DIRL: Domain-Invariant Representation Learning Domain-Invariant Representation Learning (DIRL) is a novel algorithm that semantically aligns both the
PyTorch implementation of SimSiam: Exploring Simple Siamese Representation Learning
SimSiam: Exploring Simple Siamese Representation Learning This is a PyTorch implementation of the SimSiam paper: @Article{chen2020simsiam, author =
The implementation of the algorithm in the paper "Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data" published in ICML 2020.
DS3L This is the code for paper "Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data" published in ICML 2020. Setups The code is implem
Deep functional residue identification
DeepFRI Deep functional residue identification Citing @article {Gligorijevic2019, author = {Gligorijevic, Vladimir and Renfrew, P. Douglas and Koscio
Source code for "MusCaps: Generating Captions for Music Audio" (IJCNN 2021)
MusCaps: Generating Captions for Music Audio Ilaria Manco1 2, Emmanouil Benetos1, Elio Quinton2, Gyorgy Fazekas1 1 Queen Mary University of London, 2
Official codes for the paper "Learning Hierarchical Discrete Linguistic Units from Visually-Grounded Speech"
ResDAVEnet-VQ Official PyTorch implementation of Learning Hierarchical Discrete Linguistic Units from Visually-Grounded Speech What is in this repo? M
Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.
Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.
Deep Learning Visuals contains 215 unique images divided in 23 categories
Deep Learning Visuals contains 215 unique images divided in 23 categories (some images may appear in more than one category). All the images were originally published in my book "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide".
TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.
TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models. The library is a collection of Keras models and supports classification, regression and ranking. TF-DF is a TensorFlow wrapper around the Yggdrasil Decision Forests C++ libraries. Models trained with TF-DF are compatible with Yggdrasil Decision Forests' models, and vice versa.
True Few-Shot Learning with Language Models
This codebase supports using language models (LMs) for true few-shot learning: learning to perform a task using a limited number of examples from a single task distribution.
Deep Image Search is an AI-based image search engine that includes deep transfor learning features Extraction and tree-based vectorized search.
Deep Image Search - AI-Based Image Search Engine Deep Image Search is an AI-based image search engine that includes deep transfer learning features Ex
PyTorch implementation of some learning rate schedulers for deep learning researcher.
pytorch-lr-scheduler PyTorch implementation of some learning rate schedulers for deep learning researcher. Usage WarmupReduceLROnPlateauScheduler Visu
AEC_DeepModel - Deep learning based acoustic echo cancellation baseline code
AEC_DeepModel - Deep learning based acoustic echo cancellation baseline code
The code for 2021 MGTV AI Challenge Anti Stealing Link, and the online result ranks 10th.
赛题介绍 芒果TV-第二届“马栏山杯”国际音视频算法大赛-防盗链 随着业务的发展,芒果的视频内容也深受网友的喜欢,不少视频网站和应用开始盗播芒果的视频内容,盗链网站不经过芒果TV的前端系统,跳过广告播放,且消耗大量的服务器、带宽资源,直接给公司带来了巨大的经济损失,因此防盗链在日常运营中显得尤为重要
Local Attention - Flax module for Jax
Local Attention - Flax Autoregressive Local Attention - Flax module for Jax Install $ pip install local-attention-flax Usage from jax import random fr
Code for our paper "Mask-Align: Self-Supervised Neural Word Alignment" in ACL 2021
Mask-Align: Self-Supervised Neural Word Alignment This is the implementation of our work Mask-Align: Self-Supervised Neural Word Alignment. @inproceed
CarolinaCon CTF Online
CarolinaCon Online CTF CTF challenges from CarolinaCon Online April 23 through April 25, 2021. All challenges from the CTF will eventually be here. Co
Bachelor's Thesis in Computer Science: Privacy-Preserving Federated Learning Applied to Decentralized Data
federated is the source code for the Bachelor's Thesis Privacy-Preserving Federated Learning Applied to Decentralized Data (Spring 2021, NTNU) Federat
Orchest is a browser based IDE for Data Science.
Orchest is a browser based IDE for Data Science. It integrates your favorite Data Science tools out of the box, so you don’t have to. The application is easy to use and can run on your laptop as well as on a large scale cloud cluster.
Multitask Learning Strengthens Adversarial Robustness
Multitask Learning Strengthens Adversarial Robustness
Implementation of "Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification"
hypergraph_reid Implementation of "Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification" If you find this help your research,
Minimal implementation of PAWS (https://arxiv.org/abs/2104.13963) in TensorFlow.
PAWS-TF 🐾 Implementation of Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples (PAWS)
When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset of 53,000+ Legal Holdings
When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset of 53,000+ Legal Holdings This is the repository for t
Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency
Image Crop Analysis This is a repo for the code used for reproducing our Image Crop Analysis paper as shared on our blog post. If you plan to use this
[CVPR'21 Oral] Seeing Out of tHe bOx: End-to-End Pre-training for Vision-Language Representation Learning
Seeing Out of tHe bOx: End-to-End Pre-training for Vision-Language Representation Learning [CVPR'21, Oral] By Zhicheng Huang*, Zhaoyang Zeng*, Yupan H
Implementation of Bidirectional Recurrent Independent Mechanisms (Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules)
BRIMs Bidirectional Recurrent Independent Mechanisms Implementation of the paper Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neura
Tensorflow implementation for Self-supervised Graph Learning for Recommendation
If the compilation is successful, the evaluator of cpp implementation will be called automatically. Otherwise, the evaluator of python implementation will be called.
IAUnet: Global Context-Aware Feature Learning for Person Re-Identification
IAUnet This repository contains the code for the paper: IAUnet: Global Context-Aware Feature Learning for Person Re-Identification Ruibing Hou, Bingpe
A GPT, made only of MLPs, in Jax
MLP GPT - Jax (wip) A GPT, made only of MLPs, in Jax. The specific MLP to be used are gMLPs with the Spatial Gating Units. Working Pytorch implementat
Implementation of the paper "Shapley Explanation Networks"
Shapley Explanation Networks Implementation of the paper "Shapley Explanation Networks" at ICLR 2021. Note that this repo heavily uses the experimenta
(L2ID@CVPR2021) Boosting Co-teaching with Compression Regularization for Label Noise
Nested-Co-teaching (L2ID@CVPR2021) Pytorch implementation of paper "Boosting Co-teaching with Compression Regularization for Label Noise" [PDF] If our
Procedural 3D data generation pipeline for architecture
Synthetic Dataset Generator Authors: Stanislava Fedorova Alberto Tono Meher Shashwat Nigam Jiayao Zhang Amirhossein Ahmadnia Cecilia bolognesi Dominik
Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CVPR 2021)
Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CAC) Xin Lai*, Zhuotao Tian*, Li Jiang, Shu Liu, Hengshuang Zhao, Li
Learning to Reconstruct 3D Manhattan Wireframes from a Single Image
Learning to Reconstruct 3D Manhattan Wireframes From a Single Image This repository contains the PyTorch implementation of the paper: Yichao Zhou, Hao