This repo is the official megengine implementation of the ECCV2022 paper: Efficient One Pass Self-distillation with Zipf's Label Smoothing.

Additional C++11 Random Distributions

Confirming that Zipf's Law is real and amazing

Code for the paper "Sampling strategies in Siamese Networks for unsupervised speech representation learning" Interspeech 2018

Language Modelling for various corpora, Natural Language Generation using LMs, Corpus Statistics Visualization

An experiment to demonstrate the biases and predictability of our world.

Paper about the generation of random numbers distributed according to the Zipf-Mandelbrot law

Persian Search Engine, Project of Information Retrieval Course

Assigmnents of CL

Zipf's law has been proven on the Turkish and English versions of Harry Potter and the Philosopher's Stone.

This package implements the threshold algorithm for decimation and collapsing of time series. If use, please cite: "Torre, I. G., Luque, B., Lacasa, L., Luque, J., & Hernández-Fernández, A. (2017). Emergence of linguistic laws in human voice. Scientific reports, 7, 43862."

Reimplementation of Manin (2008)'s models of lexical-semantic evolution

Análisis de 'El Señor de los Anillos' mediante la Ley de Zipf: un estudio detallado de la distribución de frecuencias de palabras en la trilogía de Tolkien para explorar la aplicabilidad de esta fascinante ley estadística en la literatura épica.

A DSL for asserting password composition policy effectiveness.

Generated pseudo text using LSTMs (Long Short Term Memory networks) and GPT-2, evaluated how close this machine-generated text is to human-generated text by checking if they follow statistical features followed by human-generated text such as Zipf’s and Heap’s Laws for Words

Implementation of unigram/bigram language models, noisy channel and pointwise mutual information for natural language processing.

从zip中读取文件,模块，支持普通require，fs等操作及各种构建工具

Dart implementation of a Zipf-distributed random number generator.

See if your Word document conforms to Zipf's Law!

Stopword Analysis on Text Mining - With dataset from Kaggle: https://www.kaggle.com/nltkdata/web-text-corpus