https://github.com/eps696/aphantasia
Learning Transferable Visual Models From Natural Language Supervision
Papers with Code 아카이브
Benchmarking
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/eric-vader/HD-BO-Additive-Models
NAS-Bench-101: Towards Reproducible Neural Architecture Search
https://github.com/ericchen321/ros_x_habitat
https://github.com/ericxumit/MGH_medical_AI
Multitask learning and benchmarking with clinical time series data
https://github.com/ericyinyzy/vlattack
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/erikbern/ann-benchmarks
ANN-Benchmarks: A Benchmarking Tool for Approximate Nearest Neighbor Algorithms
https://github.com/errec-sun/mnist
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
https://github.com/estrellaxyu/differential-alignment-for-daod
Align and Distill: Unifying and Improving Domain Adaptive Object Detection
https://github.com/etendue/habitat-api
https://github.com/eth-pbl/tinyissimoyolo
Ultra-Efficient On-Device Object Detection on AI-Integrated Smart Glasses with TinyissimoYOLO
https://github.com/ethz-asl/hf_net
Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions
https://github.com/ethz-asl/hfnet
Benchmarking 6DOF Outdoor Visual Localization in Changing Conditions
https://github.com/evavanweenen/u-net
https://github.com/everything2x/realsr-ncnn-vulkan-python
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
https://github.com/eynaij/mmdetection
https://github.com/eynaij/mmdetection_he
https://github.com/fabianwinter93/JAX/tree/main/FastFeedForwardNetwork
https://github.com/facebookresearch/augmentation-corruption
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
https://github.com/facebookresearch/brainmagick
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/facebookresearch/clip-rocket
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/facebookresearch/disentangling-correlated-factors
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
https://github.com/facebookresearch/habitat-api
https://github.com/facebookresearch/habitat-challenge
https://github.com/facebookresearch/habitat-lab
https://github.com/facebookresearch/meta_secalign
InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents
https://github.com/facebookresearch/metaicl
Multitask Prompted Training Enables Zero-Shot Task Generalization
https://github.com/facebookresearch/multimodal_rewardbench
SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension
https://github.com/facebookresearch/soundspaces-challenge
https://github.com/facebookresearch/ssl-relation-prediction
https://github.com/facebookresearch/vissl
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/fangyi-chen/sqr
https://github.com/fanq15/GCoNet
https://github.com/farbodtaymouri/BERT-GAN
An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction
https://github.com/fastscience-ai/medflamingo
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/fchollet/arc-agi
https://github.com/feedbackward/addro
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.