https://github.com/tiger-tiger/MOSES-2020
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Papers with Code 아카이브
Benchmarking
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/tomektarabasz/deep_person_reid
Torchreid: A Library for Deep Learning Person Re-Identification in Pytorch
https://github.com/tomomasayamasaki/RBFleX-NAS
NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size
https://github.com/towhee-io/towhee
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/treelli/apt
https://github.com/trougnouf/mthesis-denoise
https://github.com/trustairlab/mgtbench
https://github.com/ttengwang/coco-caption
https://github.com/ttppss/mmdetection
https://github.com/ttusar/coco
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting
https://github.com/ttusar/coco-gbea
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting
https://github.com/tu184044109/BVQA_Benchmark
UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content
https://github.com/tue-mps/vfm-uda
How to Benchmark Vision Foundation Models for Semantic Segmentation?
https://github.com/tuetschek/e2e-metrics
https://github.com/tumaer/jax-sph
LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite
https://github.com/twitter-research/multilingual-alignment-tpp
https://github.com/tylin/coco-caption
https://github.com/uber/ludwig
Personalized Benchmarking with the Ludwig Benchmarking Toolkit
https://github.com/udaydutt12/Neural-Nets
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
https://github.com/uds-lsv/menyo-20k_mt
The Effect of Domain and Diacritics in Yorùbá-English Neural Machine Translation
https://github.com/ukplab/5pils
HintsOfTruth: A Multimodal Checkworthiness Detection Dataset with Real and Synthetic Claims
https://github.com/ukplab/arxiv2022-context-injection-stance
Multitask Prompted Training Enables Zero-Shot Task Generalization
https://github.com/unilight/s3prl-vc
S3PRL-VC: Open-source Voice Conversion Framework with Self-supervised Speech Representations
https://github.com/unveilx/slm-od-ml-comparison
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks
https://github.com/urbaneman/mmdetection_mobilenet
https://github.com/vaseline555/Federated-Learning-in-PyTorch
https://github.com/vikashchalla123/mmdet_b1.2.0_fork
https://github.com/vislearn/multi-matching-optimization
https://github.com/vividwalker/Multi-Head-Rag
https://github.com/vkartik97/habitat-challenge-two-docker
https://github.com/vlomonaco/US-TransportationMode
Custom Dual Transportation Mode Detection by Smartphone Devices Exploiting Sensor Diversity
https://github.com/vrama91/cider
https://github.com/vrama91/coco-caption
https://github.com/vrunm/text-classification-financial-phrase-bank
https://github.com/vztu/BVQA_Benchmark
UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content
https://github.com/vztu/VIDEVAL
UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.