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MIR@MU (@MIR-MU)

MIR-MU

Stars
103
Global Org. Rank 57,180 (Top 19 %)
Registered over 6 years ago
Most used languages

Jupyter Notebook
33.3 %

Python
27.8 %

Java
22.2 %

HTML
11.1 %

Shell
5.6 %
Location 🇨🇿 Czechia
Country Total Rank 966
Country Ranking

Jupyter Notebook
50

Shell
62

HTML
119

Java
182

Python
422

ffmpeg-tensorflow

Dockerfile for FFMpeg with Libtensorflow

seqrep

Scientific framework for representation in sequential data

MathMLCan

Canonicalizes different MathML encodings of equivalent formulae

MIaS

Indexes text with math in Lucene/Solr-based full-text search engines

regularized-embeddings

Experimental code for the “Text classification with word embedding regularization and soft similarity measure” (Novotný et al., 2020) paper

Jupyter Notebook

pv211-utils

Utilities for the term project in the PV211 introduction to information retrieval course

pine

A python package that allows you to train, use, and evaluate position-independent word embeddings (PInE).

Jupyter Notebook

WebMIaS

Provides a web interface for MIaS

MIaSMath

Adds math processing capabilities to Lucene or Solr

MathMLUnificator

Generalizes distinct mathematical formulae so that they can be structurally unified

MathMLCanEval

Provides a web application for the evaluation of the MathML Canonicalizer

isbiased

A library to measure biases of question answering models.

Jupyter Notebook

ARQMath-data-preprocessing

Preprocessed ARQMath competition datasets

fasttext-optimizer

Suggests subword sizes for fastText language models using character n-gram frequency analysis.

Jupyter Notebook

regemt

Regressive ensemble for machine translation evaluation

Jupyter Notebook

CompuBERT

Adaptation of Transformers architecture to resolve ARQMath CLEF 2020 Competition: Answer Retrieval and Formula Search

Jupyter Notebook

ARQMath-eval

Evaluation of systems for the ARQMath competition

softalign_objectives

Implementation of ACL 2023's paper: Soft Alignment Objectives for Robust Adaptation of Language Generation