GRaNDPapA: Generator of Rad Names from Decent Paper Acronyms

Overview

GRaNDPapA: Generator of Rad Names from Decent Paper Acronyms

Trying to publish a new machine learning model and can't write a decent title for your paper?
Are all of your titles just sequences of 10 keywords?
Jealous of the cool kids with their sweet paper names like "ALBERT" and "ELMo"?
Well look no further, GRaNDPapA will take whatever buzzwords you want in the title and make a cool Acronym out of it.

Examples:

  • GRaNDPapA: Generator of Rad Names from Decent Paper Acronyms
  • LaSAgNe Clustering: Language Space Agnostic News Clustering
  • SeAtBeLT: Sentence Attention for Bert Label Transformers
  • ReCUsAntS: Rejuvenation of Cells Using Ant Saliva

Usage:

  1. Install python 3
  2. Clone this repository
  3. Run python3 main.py
  4. Input the set of keywords you want in your acronym

Extra parameters:

Preserve word order: If true, will only create acronyms that maintain the provided word order.
Warning: If false, pay attention to the exponential growth of the number of possible permutations for longer lists of words.

Force use of all words: If true, will ensure all words are used in the Acronym.
Warning: There is a known bug that sometimes acronyms can be generated that are missing the last word.

Implementation details:

For efficiency, a tree is constructed to represent all the words in the English language.
Each word string will represent a path down this tree and will end in a node labeled as "final" if the word exists.
Each node keeps track of all outgoing letters that lead to possible words from that point.
When the document words are introduced, this tree is intersected with the tree of possible acronyms for those words.
At each node, only outgoing nodes that follow the rules of the Acronym generation are maintained.
Paths down this intersected tree to final nodes are words that exist in the English language and are valid acronyms for the given words.

Credits

Developed for Priberam Labs
List of all English words by dwyl

Self-supervised Product Quantization for Deep Unsupervised Image Retrieval - ICCV2021

Self-supervised Product Quantization for Deep Unsupervised Image Retrieval Pytorch implementation of SPQ Accepted to ICCV 2021 - paper Young Kyun Jang

Young Kyun Jang 71 Dec 27, 2022
Code for "Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification", ECCV 2020 Spotlight

Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification Implementation of "Learning From Multiple Experts: Se

27 Nov 05, 2022
Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation

Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation [Arxiv] [Video] Evaluation code for Unrestricted Facial Geometry Reconstr

Matan Sela 242 Dec 30, 2022
Time-series-deep-learning - Developing Deep learning LSTM, BiLSTM models, and NeuralProphet for multi-step time-series forecasting of stockĀ price.

Stock Price Prediction Using Deep Learning Univariate Time Series Predicting stock price using historical data of a company using Neural networks for

Abdultawwab Safarji 7 Nov 27, 2022
pytorch implementation of the ICCV'21 paper "MVTN: Multi-View Transformation Network for 3D Shape Recognition"

MVTN: Multi-View Transformation Network for 3D Shape Recognition (ICCV 2021) By Abdullah Hamdi, Silvio Giancola, Bernard Ghanem Paper | Video | Tutori

Abdullah Hamdi 64 Jan 03, 2023
Official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Recognition" in AAAI2022.

AimCLR This is an official PyTorch implementation of "Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Reco

Gty 44 Dec 17, 2022
Employs neural networks to classify images into four categories: ship, automobile, dog or frog

Neural Net Image Classifier Employs neural networks to classify images into four categories: ship, automobile, dog or frog Viterbi_1.py uses a classic

Riley Baker 1 Jan 18, 2022
DiAne is a smart fuzzer for IoT devices

Diane Diane is a fuzzer for IoT devices. Diane works by identifying fuzzing triggers in the IoT companion apps to produce valid yet under-constrained

seclab 28 Jan 04, 2023
The implemention of Video Depth Estimation by Fusing Flow-to-Depth Proposals

Flow-to-depth (FDNet) video-depth-estimation This is the implementation of paper Video Depth Estimation by Fusing Flow-to-Depth Proposals Jiaxin Xie,

32 Jun 14, 2022
Music library streaming app written in Flask & VueJS

djtaytay This is a little toy app made to explore Vue, brush up on my Python, and make a remote music collection accessable through a web interface. I

Ryan Tasson 6 May 27, 2022
Official Repository for the paper "Improving Baselines in the Wild".

iWildCam and FMoW baselines (WILDS) This repository was originally forked from the official repository of WILDS datasets (commit 7e103ed) For general

Kazuki Irie 3 Nov 24, 2022
Python wrapper to access the amazon selling partner API

PYTHON-AMAZON-SP-API Amazon Selling-Partner API If you have questions, please join on slack Contributions very welcome! Installation pip install pytho

Michael Primke 330 Jan 06, 2023
Match SafeGraph POIs with Data collected through a cultural resource survey in Washington DC.

Match SafeGraph POI data with Cultural Resource Places in Washington DC Match SafeGraph POIs with Data collected through a cultural resource survey in

Changjie Chen 1 Jan 05, 2022
Group-Free 3D Object Detection via Transformers

Group-Free 3D Object Detection via Transformers By Ze Liu, Zheng Zhang, Yue Cao, Han Hu, Xin Tong. This repo is the official implementation of "Group-

Ze Liu 213 Dec 07, 2022
FaceQgen: Semi-Supervised Deep Learning for Face Image Quality Assessment

FaceQgen FaceQgen: Semi-Supervised Deep Learning for Face Image Quality Assessment This repository is based on the paper: "FaceQgen: Semi-Supervised D

Javier Hernandez-Ortega 3 Aug 04, 2022
Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark (ICCV 2021)

Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark (ICCV 2021) Kun Wang, Zhenyu Zhang, Zhiqiang Yan, X

kunwang 66 Nov 24, 2022
The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding"

AutoSF The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding" and this paper has been accepted by ICDE2020. News:

AutoML Research 64 Dec 17, 2022
A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.

Visdom A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Python. Overview Concepts Setup Usage API To

FOSSASIA 9.4k Jan 07, 2023
A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image Domains (IJCV submission)

wsss-analysis The code of: A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image Domains, arXiv pre-print 2019 paper.

Lyndon Chan 48 Dec 18, 2022