Papers with Code 아카이브

Benchmarking

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

2

보존된 평가 기록

2

코드

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

https://github.com/Boese0601/DUT_AI_2020_mmdetection

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/BrightBlueCheese/Modeling-of-Time-varying-Wireless-Communication-Channel-with-Fading-and-Shadowing

The Role of Model Architecture and Scale in Predicting Molecular Properties: Insights from Fine-Tuning RoBERTa, BART, and LLaMA

https://github.com/ByteSumoLtd/pyESN

Echo State Networks with Self-Normalizing Activations on the Hyper-Sphere

https://github.com/CAMMA-public/cholect50

Data Splits and Metrics for Method Benchmarking on Surgical Action Triplet Datasets

https://github.com/CHNPAT005/PCEPTG-MSC

Malliavin-Mancino estimators implemented with non-uniform fast Fourier transforms

https://github.com/CXH-Research/UIE-UnFold

Implicit Multi-Spectral Transformer: An Lightweight and Effective Visible to Infrared Image Translation Model

https://github.com/Capsar/DL-GenISP

GenISP: Neural ISP for Low-Light Machine Cognition

https://github.com/ChangWeiTan/TS-Extrinsic-Regression

Monash University, UEA, UCR Time Series Extrinsic Regression Archive

https://github.com/ClimbsRocks/auto_ml

Benchmarking Automatic Machine Learning Frameworks

https://github.com/CogComp/BenchmarkingZeroShot

Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach

https://github.com/D-X-Y/NATS-Bench

NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size

https://github.com/D3-AI/Orion

AER: Auto-Encoder with Regression for Time Series Anomaly Detection

https://github.com/DIG-Beihang/RobustART

RobustART: Benchmarking Robustness on Architecture Design and Training Techniques

https://github.com/Daffan/ros_jackal

Benchmarking Reinforcement Learning Techniques for Autonomous Navigation

https://github.com/Dam930/rllab

Benchmarking Deep Reinforcement Learning for Continuous Control

https://github.com/DataXujing/Cascade_RCNN_mmdetection

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/DaveFClarke/ml_bias_checking

AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

https://github.com/DaveKim3872/nasbench-hpc

NAS-Bench-101: Towards Reproducible Neural Architecture Search

https://github.com/Davidnet/TFSegmentation

RTSeg: Real-time Semantic Segmentation Comparative Study

https://github.com/DecentMakeover/detection

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/DecentMakeover/mdetect

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/DeepMicroscopy/nnUNet

nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation

https://github.com/Denys88/rl_games

The StarCraft Multi-Agent Challenge

https://github.com/DevSinghSachan/art

Multitask Prompted Training Enables Zero-Shot Task Generalization

https://github.com/DhruvMakwana/Global-Wheat-Detection

Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high resolution RGB labelled images to develop and benchmark wheat head detection methods

https://github.com/Diegomangasco/Vision-Language-AML

Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation

https://github.com/Dongdongshe/mlfuzz

Revisiting Neural Program Smoothing for Fuzzing

https://github.com/Dongximing/Mimic3

Multitask learning and benchmarking with clinical time series data

https://github.com/DoubleBlindGithub/M3

Multitask learning and benchmarking with clinical time series data

https://github.com/EPFL-VILAB/XDEnsembles

Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

https://github.com/ESBigeard/paper_graph

BioSentVec: creating sentence embeddings for biomedical texts

https://github.com/Edge-AI-Acceleration-Lab/RBFleX-NAS

NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size

https://github.com/ElliotY-ML/Hippocampus_Segmentation_MRI

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

https://github.com/EmreTaha/shortcut-perspective-TF2

Shortcut Learning in Deep Neural Networks

https://github.com/EpistasisLab/tpot

Benchmarking Automatic Machine Learning Frameworks

https://github.com/EvgeniyaMartynova/MLiP_M5

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

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