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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/MindSpore-scientific-2/code-12/tree/main/MCA

MCA-Bench: A Multimodal Benchmark for Evaluating CAPTCHA Robustness Against VLM-based Attacks

https://github.com/MindSpore-scientific-2/code-14/tree/main/graphormer

Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets

https://github.com/MindSpore-scientific/code-13/tree/main/signSGD

signSGD with Majority Vote is Communication Efficient And Fault Tolerant

https://github.com/Mohit-Mithra/AuthNet

AuthNet: A Deep Learning based Authentication Mechanism using Temporal Facial Feature Movements

https://github.com/MonashAI/LIT

Fast Vision Transformers with HiLo Attention

https://github.com/Muhammad-Huzaifaa/ObjectCompose

ImageNet-E: Benchmarking Neural Network Robustness via Attribute Editing

https://github.com/MustaphaBounoua/minde

Beyond Normal: On the Evaluation of Mutual Information Estimators

https://github.com/NBAiLab/notram

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

https://github.com/NYU-DICE-Lab/open_clip

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/OML-Team/open-metric-learning

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/OceanPang/Libra_R-CNN

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/OlineRanum/SAPA

Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison

https://github.com/Orange-OpenSource/carla_croco_vcnet

CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms

https://github.com/PaddlePaddle/PASSL/blob/main/docs/Train_CLIP_model.md

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/PaddlePaddle/PGL

Benchmarking Graph Neural Networks

https://github.com/PaddlePaddle/PGL/tree/main/ogb_examples/graphproppred/ogbg_molpcba

Benchmarking Graph Neural Networks

https://github.com/PaddlePaddle/PGL/tree/main/ogb_examples/nodeproppred/ogbn-arxiv/unimp_appnp_vnode_smooth

Benchmarking Graph Neural Networks

https://github.com/PaddlePaddle/PGL/tree/main/ogb_examples/nodeproppred/ogbn-proteins/unimp_cross_feat

Benchmarking Graph Neural Networks

https://github.com/PaddlePaddle/PGL/tree/master/examples/GaAN

Benchmarking Graph Neural Networks

https://github.com/PaddlePaddle/PGL/tree/master/ogb_examples/nodeproppred/ogbn-arxiv

Benchmarking Graph Neural Networks

https://github.com/PaddlePaddle/PaddleFL

LEAF: A Benchmark for Federated Settings

https://github.com/PaddlePaddle/PaddleScience

DrivAerNet++: A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks

https://github.com/PathologyDataScience/NuCLS

NuCLS: A scalable crowdsourcing, deep learning approach and dataset for nucleus classification, localization and segmentation

https://github.com/Pavyel/Novelty-Detection

TAP-DLND 1.0 : A Corpus for Document Level Novelty Detection

https://github.com/PennyLaneAI/pennylane

Better than classical? The subtle art of benchmarking quantum machine learning models

https://github.com/PermiJW/signSGD-with-Majority-Vote

signSGD with Majority Vote is Communication Efficient And Fault Tolerant

https://github.com/PolyAI-LDN/polyai-models

Benchmarking Natural Language Understanding Services for building Conversational Agents

https://github.com/PolyAI-LDN/task-specific-datasets

Benchmarking Natural Language Understanding Services for building Conversational Agents

https://github.com/Precision-Medical-Imaging-Group/HOPE-Segmenter-Kids

Magnetic Resonance Imaging Feature-Based Subtyping and Model Ensemble for Enhanced Brain Tumor Segmentation

https://github.com/ProhetTeam/QuantMmdetection

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/QCOIN-LAB/E2ECPE

End-to-end Emotion-Cause Pair Extraction via Learning to Link

https://github.com/RF5/CurveNet

Benchmarking Robustness of 3D Point Cloud Recognition Against Common Corruptions

https://github.com/RUCAIBox/RecBole

RecBole 2.0: Towards a More Up-to-Date Recommendation Library

https://github.com/Rajwrita/Brain-Tumor-Auto-Segmentation

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

https://github.com/RangiLyu/mmdetection_test

MMDetection: Open MMLab Detection Toolbox and Benchmark

https://github.com/RasaHQ/rasa

Benchmarking Natural Language Understanding Services for building Conversational Agents

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