DECAF: Deep Extreme Classification with Label Features

Related tags

Deep Learningpythonmachine-learningdeep-learningclassificationmulti-label-classificationdecafmeta-dataextreme-classificationlabel-textlabel-features
Overview

DECAF

DECAF: Deep Extreme Classification with Label Features

@InProceedings{Mittal21,
    author = "Mittal, A. and Dahiya, K. and Agrawal, S. and Saini, D. and Agarwal, S. and Kar, P. and Varma, M.",
    title = "DECAF: Deep Extreme Classification with Label Features",
    booktitle = "Proceedings of the ACM International Conference on Web Search and Data Mining",
    month = "March",
    year = "2021",
    }

SETUP WORKSPACE

mkdir -p ${HOME}/scratch/XC/data 
mkdir -p ${HOME}/scratch/XC/programs

SETUP DECAF

cd ${HOME}/scratch/XC/programs
git clone https://github.com/Extreme-classification/DECAF.git
conda create -f DECAF/decaf_env.yml
conda activate decaf
git clone https://github.com/kunaldahiya/pyxclib.git
cd pyxclib
python setup.py install
cd ../DECAF

DOWNLOAD DATASET

cd ${HOME}/scratch/XC/data
gdown --id <dataset id>
unzip *.zip
dataset dataset id
LF-AmazonTitles-131K 1VlfcdJKJA99223fLEawRmrXhXpwjwJKn
LF-WikiSeeAlsoTitles-131K 1edWtizAFBbUzxo9Z2wipGSEA9bfy5mdX
LF-AmazonTitles-1.3M 1Davc6BIfoTIAS3mP1mUY5EGcGr2zN2pO

RUNNING DECAF

cd ${HOME}/scratch/XC/programs/DECAF
chmod +x run_DECAF.sh
./run_DECAF.sh <gpu_id> <DECAF TYPE> <dataset> <folder name>
e.g.
./run_DECAF.sh 0 DECAF LF-AmazonTitles-131K DECAF_RUN
./run_DECAF.sh 0 DECAF-lite LF-AmazonTitles-131K DECAF_RUN
Owner
GitHub Repository
Generative Query Network (GQN) in PyTorch as described in "Neural Scene Representation and Rendering"

Update 2019/06/24: A model trained on 10% of the Shepard-Metzler dataset has been added, the following notebook explains the main features of this mod

Jesper Wohlert 313 Dec 27, 2022
A parametric soroban written with CADQuery.

A parametric soroban written in CADQuery The purpose of this project is to demonstrate how "code CAD" can be intuitive to learn. See soroban.py for a

Lee 4 Aug 13, 2022
Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks

Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks This is a Pytorch-Lightning implementation of the paper "Self-s

Photogrammetry & Robotics Bonn 111 Dec 06, 2022
NIMA: Neural IMage Assessment

PyTorch NIMA: Neural IMage Assessment PyTorch implementation of Neural IMage Assessment by Hossein Talebi and Peyman Milanfar. You can learn more from

Kyryl Truskovskyi 293 Dec 30, 2022
Pre-trained Deep Learning models and demos (high quality and extremely fast)

OpenVINO™ Toolkit - Open Model Zoo repository This repository includes optimized deep learning models and a set of demos to expedite development of hi

OpenVINO Toolkit 3.4k Dec 31, 2022
[NeurIPS2021] Code Release of Learning Transferable Perturbations

Learning Transferable Adversarial Perturbations This is an official release of the paper Learning Transferable Adversarial Perturbations. The code is

Krishna Kanth 17 Nov 11, 2022
Toolbox of models, callbacks, and datasets for AI/ML researchers.

Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch Website • Installation • Main

Pytorch Lightning 1.4k Dec 30, 2022
QQ Browser 2021 AI Algorithm Competition Track 1 1st Place Program

QQ Browser 2021 AI Algorithm Competition Track 1 1st Place Program

249 Jan 03, 2023
Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.

Object tracking implemented with YOLOv4, DeepSort, and TensorFlow. YOLOv4 is a state of the art algorithm that uses deep convolutional neural networks to perform object detections. We can take the ou

The AI Guy 1.1k Dec 29, 2022
Explaining in Style: Training a GAN to explain a classifier in StyleSpace

Explaining in Style: Official TensorFlow Colab Explaining in Style: Training a GAN to explain a classifier in StyleSpace Oran Lang, Yossi Gandelsman,

Google 197 Nov 08, 2022
Interpretation of T cell states using reference single-cell atlases

Interpretation of T cell states using reference single-cell atlases ProjecTILs is a computational method to project scRNA-seq data into reference sing

Cancer Systems Immunology Lab 139 Jan 03, 2023
Count the MACs / FLOPs of your PyTorch model.

THOP: PyTorch-OpCounter How to install pip install thop (now continously intergrated on Github actions) OR pip install --upgrade git+https://github.co

Ligeng Zhu 3.9k Dec 29, 2022
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

Xinyi Wang 21 May 18, 2022
CFNet: Cascade and Fused Cost Volume for Robust Stereo Matching（CVPR2021）

CFNet(CVPR 2021) This is the implementation of the paper CFNet: Cascade and Fused Cost Volume for Robust Stereo Matching, CVPR 2021, Zhelun Shen, Yuch

106 Dec 28, 2022
Project page for End-to-end Recovery of Human Shape and Pose

End-to-end Recovery of Human Shape and Pose Angjoo Kanazawa, Michael J. Black, David W. Jacobs, Jitendra Malik CVPR 2018 Project Page Requirements Pyt

1.4k Dec 29, 2022
Official PyTorch implementation of StyleGAN3

Modified StyleGAN3 Repo Changes Made tied to python 3.7 syntax .jpgs instead of .pngs for training sample seeds to recreate the 1024 training grid wit

Derrick Schultz (he/him) 83 Dec 15, 2022
PyTorch-centric library for evaluating and enhancing the robustness of AI technologies

Responsible AI Toolbox A library that provides high-quality, PyTorch-centric tools for evaluating and enhancing both the robustness and the explainabi

24 Dec 22, 2022
Collision risk estimation using stochastic motion models

collision_risk_estimation Collision risk estimation using stochastic motion models. This is a new approach, based on stochastic models, to predict the

Unmesh 7 Jun 26, 2022
Mercury: easily convert Python notebook to web app and share with others

Mercury Share your Python notebooks with others Easily convert your Python notebooks into interactive web apps by adding parameters in YAML. Simply ad

MLJAR 2.2k Dec 27, 2022
🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱

Monitor deep learning model training and hardware usage from mobile. 🔥 Features Monitor running experiments from mobile phone (or laptop) Monitor har

labml.ai 1.2k Dec 25, 2022