Estonian Grammatical Error Correction (GEC) test and development corpus that contains L2 learner texts error-annotated in the M2 format.
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Updated
May 25, 2024 - Python
Estonian Grammatical Error Correction (GEC) test and development corpus that contains L2 learner texts error-annotated in the M2 format.
A Python toolkit for setting up benchmarking dataset using biomedical networks
Supplementary material for our paper "THERE IS NO DATA LIKE MORE DATA" is provided.
A framework for benchmarking clustering algorithms – Benchmark results (for version 1 of the Suite)
BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks
Source code for experiments in the papers "Beyond Benchmarks: Assessing Knowledge Graph Completion Methods on Non-Benchmark Employee Data" (IEEE 2024, yet to be published)
The official repository for the CBM paper "Deep Reinforcement Learning Enables Better Bias Control in Benchmark for Virtual Screening".
Classical benchmark sets for the one-dimensional bin packing problem
Launched in March 2020 in response to the coronavirus disease 2019 (COVID-19) pandemic, COVID-Net is a global open source, open access initiative dedicated to accelerating advancement in machine learning to aid front-line healthcare workers and clinical institutions around the world fighting the continuing pandemic. Towards this goal, our global…
Properly pre-processed full-scale Freebase datasets
Repository for the paper "ViHOS: Vietnamese Hate and Offensive Spans Detection" (EACL2023)
A PyTorch toolbox for domain generalization, domain adaptation and semi-supervised learning.
A framework for benchmarking clustering algorithms – Benchmark suite, version 1
A Rust port of NASBench: https://github.com/google-research/nasbench
benchmark dataset and Deep learning method (Hierarchical Interaction Network, HINT) for clinical trial approval probability prediction, published in Cell Patterns 2022.
Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
This is the official repository for evaluation on the NoW Benchmark Dataset. The goal of the NoW benchmark is to introduce a standard evaluation metric to measure the accuracy and robustness of 3D face reconstruction methods from a single image under variations in viewing angle, lighting, and common occlusions.
Notebooks gerados para o meu TCC no curso de graduação Sistemas e Mídias Digitais da Universidade Federal do Ceará.
This repository contains the collection of UCI (real-life) datasets and Synthetic (artificial) datasets (with cluster labels and MATLAB files) ready to use with clustering algorithms.
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