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Benchmarking

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/arodio/ca-fed

Federated Learning Under Intermittent Client Availability and Time-Varying Communication Constraints

https://github.com/aronfothi/mask_cluster_rcnn

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/arsalan993/Multivariate-timeseries-forecasting-using-TS-decompostion-and-deep-learnring

Forecasting Across Time Series Databases using Recurrent Neural Networks on Groups of Similar Series: A Clustering Approach

https://github.com/arsalan993/Univariate-Time-Series-Forecasting-using-decomposition-and-Deep-Learning

Forecasting Across Time Series Databases using Recurrent Neural Networks on Groups of Similar Series: A Clustering Approach

https://github.com/artefactory/choice-learn

A Neural-embedded Choice Model: TasteNet-MNL Modeling Taste Heterogeneity with Flexibility and Interpretability

https://github.com/artyompal/kaggle-abstract-reasoning

On the Measure of Intelligence

https://github.com/arunppsg/TadGAN

TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks

https://github.com/aslialp/HATCNN

Torchreid: A Library for Deep Learning Person Re-Identification in Pytorch

https://github.com/assassint2017/MICCAI-LITS2017

The Liver Tumor Segmentation Benchmark (LiTS)

https://github.com/assulthoni/TweetSentimentIndoBERT

IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding

https://github.com/atreyasha/mimic3_benchmarks_occlusion

Multitask learning and benchmarking with clinical time series data

https://github.com/atreyasha/mv-temporal-rgan

Multitask learning and benchmarking with clinical time series data

https://github.com/autogluon/tabrepo

TabArena: A Living Benchmark for Machine Learning on Tabular Data

https://github.com/automl/auto-sklearn

Benchmarking Automatic Machine Learning Frameworks

https://github.com/automl/nes

Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

https://github.com/avouros/clustering-workplace

An empirical comparison between stochastic and deterministic centroid initialisation for K-Means variations

https://github.com/aws-samples/amazon-sagemaker-spleen-image-segmentation

A large annotated medical image dataset for the development and evaluation of segmentation algorithms

https://github.com/axiomlab/Cable

MS MARCO: A Human Generated MAchine Reading COmprehension Dataset

https://github.com/ayeshakhtar209/fashion-mnist

Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

https://github.com/azibit/detection

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/azshue/TPT

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/b4shy/Medical

A large annotated medical image dataset for the development and evaluation of segmentation algorithms

https://github.com/baai-zlab/coig

Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

https://github.com/balakg/transects-eccv2020

Towards causal benchmarking of bias in face analysis algorithms

https://github.com/balamurugan0714/TensorFlow

Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

https://github.com/bald6354/edncnn

Event Probability Mask (EPM) and Event Denoising Convolutional Neural Network (EDnCNN) for Neuromorphic Cameras

https://github.com/bartn8/vppstereo

Active-Passive SimStereo -- Benchmarking the Cross-Generalization Capabilities of Deep Learning-based Stereo Methods

https://github.com/basf/chemteb

MTEB: Massive Text Embedding Benchmark

https://github.com/baskargroup/Arboretum

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/baskargroup/biotrove

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/beapc18/AffordanceNet

Recognizing Object Affordances to Support Scene Reasoning for Manipulation Tasks

https://github.com/beibuwandeluori/DFGC_Detection

DFGC 2021: A DeepFake Game Competition

https://github.com/beir-cellar/beir

BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models

https://github.com/benediktstroebl/inference-scaling-limits

Beyond Correctness: Benchmarking Multi-dimensional Code Generation for Large Language Models

https://github.com/bespontaneous/proteus-pytorch

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/betterzhou/AAGNN

BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.