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

Decision Tree Regression algorithm implemented on Python from scratch.

Decision_Tree_Regression I implemented the decision tree regression algorithm on Python. Unlike regular linear regression, this algorithm is used when

1 Dec 22, 2021
vortex particles for simulating smoke in 2d

vortex-particles-method-2d vortex particles for simulating smoke in 2d -vortexparticles_s

12 Aug 23, 2022
Automatically create Faiss knn indices with the most optimal similarity search parameters.

It selects the best indexing parameters to achieve the highest recalls given memory and query speed constraints.

Criteo 419 Jan 01, 2023
MLFlow in a Dockercontainer based on Azurite and Postgres

mlflow-azurite-postgres docker This is a MLFLow image which works with a postgres DB and a local Azure Blob Storage Instance (Azurite). This image is

2 May 29, 2022
MiniTorch - a diy teaching library for machine learning engineers

This repo is the full student code for minitorch. It is designed as a single repo that can be completed part by part following the guide book. It uses

1.1k Jan 07, 2023
Optimal Randomized Canonical Correlation Analysis

ORCCA Optimal Randomized Canonical Correlation Analysis This project is for the python version of ORCCA algorithm. It depends on Numpy for matrix calc

Yinsong Wang 1 Nov 21, 2021
It is a forest of random projection trees

rpforest rpforest is a Python library for approximate nearest neighbours search: finding points in a high-dimensional space that are close to a given

Lyst 211 Dec 29, 2022
Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc)

Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc). Structured a custom ensemble model and a neural network. Found a outperformed

Chris Yuan 1 Feb 06, 2022
scikit-learn: machine learning in Python

scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license. The project was started

neurodata 3 Dec 16, 2022
ML Kaggle Titanic Problem using LogisticRegrission

-ML-Kaggle-Titanic-Problem-using-LogisticRegrission here you will find the solution for the titanic problem on kaggle with comments and step by step c

Mahmoud Nasser Abdulhamed 3 Oct 23, 2022
AutoOED: Automated Optimal Experiment Design Platform

AutoOED is an optimal experiment design platform powered with automated machine learning to accelerate the discovery of optimal solutions. Our platform solves multi-objective optimization problems an

Yunsheng Tian 107 Jan 03, 2023
TorchDrug is a PyTorch-based machine learning toolbox designed for drug discovery

A powerful and flexible machine learning platform for drug discovery

MilaGraph 1.1k Jan 08, 2023
QML: A Python Toolkit for Quantum Machine Learning

QML is a Python2/3-compatible toolkit for representation learning of properties of molecules and solids.

176 Dec 09, 2022
Greykite: A flexible, intuitive and fast forecasting library

The Greykite library provides flexible, intuitive and fast forecasts through its flagship algorithm, Silverkite.

LinkedIn 1.7k Jan 04, 2023
Mortality risk prediction for COVID-19 patients using XGBoost models

Mortality risk prediction for COVID-19 patients using XGBoost models Using demographic and lab test data received from the HM Hospitales in Spain, I b

1 Jan 19, 2022
nn-Meter is a novel and efficient system to accurately predict the inference latency of DNN models on diverse edge devices

A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.

Microsoft 241 Dec 26, 2022
Visualize classified time series data with interactive Sankey plots in Google Earth Engine

sankee Visualize changes in classified time series data with interactive Sankey plots in Google Earth Engine Contents Description Installation Using P

Aaron Zuspan 76 Dec 15, 2022
Python library for multilinear algebra and tensor factorizations

scikit-tensor is a Python module for multilinear algebra and tensor factorizations

Maximilian Nickel 394 Dec 09, 2022
dirty_cat is a Python module for machine-learning on dirty categorical variables.

dirty_cat dirty_cat is a Python module for machine-learning on dirty categorical variables.

637 Dec 29, 2022
Dual Adaptive Sampling for Machine Learning Interatomic potential.

DAS Dual Adaptive Sampling for Machine Learning Interatomic potential. How to cite If you use this code in your research, please cite this using: Hong

6 Jul 06, 2022