Python Contrastive-predictive-coding Resources

TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig

Contrastive Learning for Cold-start Recommendation This is our Pytorch implementation for the paper: Yinwei Wei, Xiang Wang, Qi Li, Liqiang Nie, Yan L

TaCL: Improve BERT Pre-training with Token-aware Contrastive Learning

Recreate the joys of Office Assistant from the comfort of the Python interpreter.

Social-NCE + CrowdNav Website | Paper | Video | Social NCE + Trajectron | Social NCE + STGCNN This is an official implementation for Social NCE: Contr

DetCo: Unsupervised Contrastive Learning for Object Detection arxiv link News Sparse RCNN+DetCo improves from 45.0 AP to 46.5 AP(+1.5) with 3x+ms trai

Parametric-Contrastive-Learning This repository contains the implementation code for ICCV2021 paper: Parametric Contrastive Learning (https://arxiv.or

RSC-Net: 3D Human Pose, Shape and Texture from Low-Resolution Images and Videos Implementation for "3D Human Pose, Shape and Texture from Low-Resoluti

Python and Javascript Coding Challenges Some leetcode questions I'm currently working on to open up my mind to better ways of problem solving. Impleme

ADGCL : Adversarial Graph Augmentation to Improve Graph Contrastive Learning Introduction This repo contains the Pytorch [1] implementation of Adversa

This is an AI that runs in the terminal. It is a voice assistant that can do common activities and can also help in your coding doubts like

Predictive Auto-scaling with OpenStack Monasca Giacomo Lanciano*, Filippo Galli, Tommaso Cucinotta, Davide Bacciu, Andrea Passarella 2021 IEEE/ACM 14t

AutoTabular AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just

Interpretable-contrastive-word-mover-s-embedding Paper Datasets Here is a Dropbox link to the datasets used in the paper: https://www.dropbox.com/sh/n

Improving Contrastive Learning on Imbalanced Data via Open-World Sampling Introduction Contrastive learning approaches have achieved great success in

MIRCO PyTorch implementation for paper: Latent Structures Mining with Contrastive Modality Fusion for Multimedia Recommendation Dependencies Python 3.

Git repositoty of the manuscript entitled Statistical quantification of confounding bias in predictive modelling by Tamas Spisak The manuscript descri

Contrastive Self-Supervised Learning on CIFAR-10 Paper "Towards the Generalization of Contrastive Self-Supervised Learning", Weiran Huang, Mingyang Yi

Contrastive Explanations for Model Interpretability This is the repository for the paper "Contrastive Explanations for Model Interpretability", about

CPC_audio This code implements the Contrast Predictive Coding algorithm on audio data, as described in the paper Unsupervised Pretraining Transfers we

Intermdiate layer matters - SSL The official repository for "Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning" paper. Downl

Contrastive Learning with Non-Semantic Negatives This repository is the official implementation of Robust Contrastive Learning Using Negative Samples

NeurIPS 2021 (Spotlight): Task-Adaptive Neural Network Search with Meta-Contrastive Learning This is an official PyTorch implementation of Task-Adapti

Decoupled-Contrastive-Learning This repository is an implementation for the loss function proposed in Decoupled Contrastive Loss paper. Requirements P

Directed Graph Contrastive Learning The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL). In this paper, we present the first con

Unbiased Classification Through Bias-Contrastive and Bias-Balanced Learning (NeurIPS 2021) Official Pytorch implementation of Unbiased Classification

Introduction PyTorch code for the ICLR 2021 paper [i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning]. @inproceedings{lee2021i

MCGC Description This is the code of "Multi-view Contrastive Graph Clustering" in NeurlPS 2021. Datasets Results ACM DBLP IMDB Amazon photos Amazon co

Core-tuning This repository is the official implementation of ``Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regular

The official code for the paper "Inverse Problems Leveraging Pre-trained Contrastive Representations" (to appear in NeurIPS 2021).

SoCo [NeurIPS 2021 Spotlight] Aligning Pretraining for Detection via Object-Level Contrastive Learning By Fangyun Wei*, Yue Gao*, Zhirong Wu, Han Hu,

[EMNLP 2021] Mirror-BERT: Converting Pretrained Language Models to universal text encoders without labels.

What is Retentioneering? Retentioneering is a Python framework and library to assist product analysts and marketing analysts as it makes it easier to

Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding

Improving Contrastive Learning on Imbalanced Data via Open-World Sampling Introduction Contrastive learning approaches have achieved great success in

Unofficial implementation: MoCo: Momentum Contrast for Unsupervised Visual Representation Learning (Paper) InsDis: Unsupervised Feature Learning via N

ArtLine The main aim of the project is to create amazing line art portraits. Sounds Intresting,let's get to the pictures!! Model-(Smooth) Model-(Quali

SimCSE: Simple Contrastive Learning of Sentence Embeddings This repository contains the code and pre-trained models for our paper SimCSE: Simple Contr

Zee Code ZCode is a custom compression algorithm I originally developed for a competition held for the Spring 2019 Datastructures and Algorithms cours

Surrogate- and Invariance-Boosted Contrastive Learning (SIB-CL) This repository contains all source code used to generate the results in the article "

Transform-Invariant Non-Negative Matrix Factorization A comprehensive Python package for Non-Negative Matrix Factorization (NMF) with a focus on learn

The CPC-big model and k-means checkpoints used in Analyzing Speaker Information in Self-Supervised Models to Improve Zero-Resource Speech Processing.

Paimon Paimon is a pixie (or script) who was made for anyone from {EPITECH} who are struggling with the Coding Style. Her goal is to assist you in you

We're Team Arson and we're using the power of predictive modeling to combat wildfires. Arson Map Inspiration There’s been a lot of wildfires in Califo

Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation This repository is the official implementation of CVPR 2021 paper:

Creating Robust Representations from Pre-Trained Image Encoders using Contrastive Learning Sriram Ravula, Georgios Smyrnis This is the code for our pr

DeCLIP Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm. Our paper is available in arxiv Updates ** Ou

Code for DetCon This repository contains code for the ICCV 2021 paper "Efficient Visual Pretraining with Contrastive Detection" by Olivier J. Hénaff,

DuoRec Code for WSDM 2022 paper, Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation. Usage Download datasets fr

Posterior predictive distributions quantify uncertainties ignored by point estimates.

Discord Server Maker Make discord server by Coding! FAQ How can i get role permissons? Open discord with chrome developer tool, go to network and clic

SubTab: Author: Talip Ucar ([email protected]) The official implementation of the paper, SubTab: Subsetting Features of Tabular Data for Self-Supervis

Predictive Modeling on Electronic Health Records(EHR) using Pytorch Overview Although there are plenty of repos on vision and NLP models, there are ve

live coding in python + supercollider

CMIC-Retrieval Code for Single Image 3D Shape Retrieval via Cross-Modal Instance and Category Contrastive Learning. ICCV 2021. Introduction In this wo

AryaBota An app to teach Python coding, that gradually allows students to transition from using commands similar to natural language, to more Pythonic

AirCode This repo contains source codes for the arXiv preprint "AirCode: A Robust Object Encoding Method" Demo Object matching comparison when the obj

AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models tabular data.

Website, Tutorials, and Docs    Uncertainty Toolbox A python toolbox for predictive uncertainty quantification, calibration, metrics, and visualizatio

Here, you can find the code for the paper 'Real-Time Multi-Contact Model Predictive Control via ADMM'. Code is currently being cleared up and optimize

easyopt is a super simple yet super powerful optuna-based Hyperparameters Optimization Framework that requires no coding.

Unofficial Pytorch Lightning implementation of Contrastive Syn-to-Real Generalization (ICLR, 2021)

SupCL-Seq 📖 Supervised Contrastive Learning for Downstream Optimized Sequence representations (SupCS-Seq) accepted to be published in EMNLP 2021, ext

CRL_EGPG Pytorch Implementation of Contrastive Representation Learning for Exemplar-Guided Paraphrase Generation We use contrastive loss implemented b

TensorFlow Similarity is a python package focused on making similarity learning quick and easy.

Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git, Kubernetes, Terraform, OpenStack, SQL, NoSQL, Azure, GCP, DNS, Elastic, Network, Virtualization. DevOps Interview Questions

Python Mini Projects A collection of easy Python small projects to help you improve your programming skills. Table Of Contents Aim Of The Project Cont

Object-aware Contrastive Learning Official PyTorch implementation of "Object-aware Contrastive Learning for Debiased Scene Representation" by Sangwoo

Feature Stylization and Domain-aware Contrastive Loss for Domain Generalization This is an official implementation of "Feature Stylization and Domain-

ANEMONE A PyTorch implementation of "ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning", CIKM-21 Dependencies python==3.6.1 dgl==

GANs for Fun Created because I can! GOAL The goal of this repo is to be freely used by ML devs to check the GAN performances without coding from scrat

Contra-OOD Code for EMNLP 2021 paper Contrastive Out-of-Distribution Detection for Pretrained Transformers. Requirements PyTorch Transformers datasets

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

GeDML is an easy-to-use generalized deep metric learning library

CrowdNav with Social-NCE This is an official implementation for the paper Social NCE: Contrastive Learning of Socially-aware Motion Representations by

Noise Contrastive Estimation for pyTorch Overview This repository contains a re-implementation of the Noise Contrastive Estimation algorithm, implemen

CoRe Created by Xumin Yu*, Yongming Rao*, Wenliang Zhao, Jiwen Lu, Jie Zhou This is the PyTorch implementation for ICCV paper Group-aware Contrastive

MERIT A PyTorch implementation of our IJCAI-21 paper Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning. Depen

KoSimCSE Korean Simple Contrastive Learning of Sentence Embeddings implementation using pytorch SimCSE Installation git clone https://github.com/BM-K/

Parametric-Contrastive-Learning This repository contains the implementation code for ICCV2021 paper: Parametric Contrastive Learning (https://arxiv.or

Contrastive Learning of Object Representations Supervisor: Prof. Dr. Gemma Roig Institutions: Goethe University CVAI - Computational Vision & Artifici

AECR-Net Contrastive Learning for Compact Single Image Dehazing, CVPR2021. Official Pytorch based implementation. Paper arxiv Pytorch Version TODO: mo

Improving Contrastive Learning by Visualizing Feature Transformation This project hosts the codes, models and visualization tools for the paper: Impro

Contrastive Learning for Many-to-many Multilingual Neural Machine Translation(mCOLT/mRASP2), ACL2021 The code for training mCOLT/mRASP2, a multilingua

PyGCL is an open-source library for graph contrastive learning (GCL), which features modularized GCL components from published papers, standardized evaluation, and experiment management.

Video Contrastive Learning with Global Context (VCLR) This is the official PyTorch implementation of our VCLR paper. Install dependencies environments

PyGCL: Graph Contrastive Learning for PyTorch PyGCL is an open-source library for graph contrastive learning (GCL), which features modularized GCL com

Gradient Cache Gradient Cache is a simple technique for unlimitedly scaling contrastive learning batch far beyond GPU memory constraint. This means tr

Object-aware Contrastive Learning Official PyTorch implementation of "Object-aware Contrastive Learning for Debiased Scene Representation" by Sangwoo

Django Sage Painless The django-sage-painless is a valuable package based on Django Web Framework & Django Rest Framework for high-level and rapid web

This repo contains the official implementation of Spatial Contrastive Learning for Few-Shot Classification (SCL), which presents of a novel contrastive learning method applied to few-shot image classification in order to learn more general purpose embeddings, and facilitate the test-time adaptation to novel visual categories.

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

An NCE implementation in pytorch About NCE Noise Contrastive Estimation (NCE) is an approximation method that is used to work around the huge computat

This is the official PyTorch implementation of the ALBEF paper [Blog]. This repository supports pre-training on custom datasets, as well as finetuning on VQA, SNLI-VE, NLVR2, Image-Text Retrieval on MSCOCO and Flickr30k, and visual grounding on RefCOCO+. Pre-trained and finetuned checkpoints are released.

CLSA CLSA is a self-supervised learning methods which focused on the pattern learning from strong augmentations. Copyright (C) 2020 Xiao Wang, Guo-Jun

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

(Work in Progress) Nix-Gui Make NixOS usable for non-technical users through a settings / package management GUI. Motives The declarative nature of Ni

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.

I-SECRET This is the implementation of the MICCAI 2021 Paper "I-SECRET: Importance-guided fundus image enhancement via semi-supervised contrastive con

Visual Python is a GUI-based Python code generator, developed on the Jupyter Notebook environment as an extension.