This repo is the official megengine implementation of the ECCV2022 paper: Efficient One Pass Self-distillation with Zipf's Label Smoothing.
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Updated
Oct 19, 2022 - Python
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
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.
Assigmnents of CL
Zipf's law has been proven on the Turkish and English versions of Harry Potter and the Philosopher's Stone.
This is a simple tool for text dataset analysis and multiple datasets comparison. Keywords: corpus, text dataset, text distribution, part-of-speech(pos), zipf's-law, distinct value, concreteness
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."
Does Zipf's Law apply to music?
Reimplementation of Manin (2008)'s models of lexical-semantic evolution
A DSL for asserting password composition policy effectiveness.
Dart implementation of a Zipf-distributed random number generator.
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.
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