https://github.com/macarbonneau/MILSurvey
공식 코드Multiple Instance Learning: A Survey of Problem Characteristics and Applications
Papers with Code 아카이브
Data-free Knowledge Distillation
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/machinelearning4health/medlane
공식 코드Benchmarking Automated Clinical Language Simplification: Dataset, Algorithm, and Evaluation
https://github.com/madakkmi/llpowershap
공식 코드LLpowershap: Logistic Loss-based Automated Shapley Values Feature Selection Method
https://github.com/madeagents/hammerbench
공식 코드HammerBench: Fine-Grained Function-Calling Evaluation in Real Mobile Device Scenarios
https://github.com/maenzhier/grecx
공식 코드GRecX: An Efficient and Unified Benchmark for GNN-based Recommendation
https://github.com/magantoine/jobskape
공식 코드JOBSKAPE: A Framework for Generating Synthetic Job Postings to Enhance Skill Matching
https://github.com/magics-lab/outeffhop
공식 코드Outlier-Efficient Hopfield Layers for Large Transformer-Based Models
https://github.com/mahmad00/disjoint-sampling-for-hyperspectral-image-classification
공식 코드https://github.com/mahmoodlab/hest
공식 코드HEST-1k: A Dataset for Spatial Transcriptomics and Histology Image Analysis
https://github.com/mahmoodlab/patho-bench
공식 코드https://github.com/mahmoodlab/trident
공식 코드https://github.com/maho3/ltu-ili
공식 코드LtU-ILI: An All-in-One Framework for Implicit Inference in Astrophysics and Cosmology
https://github.com/mail-ecnu/text-gym-agents
공식 코드Can language agents be alternatives to PPO? A Preliminary Empirical Study On OpenAI Gym
https://github.com/maitrix-org/de-arena
공식 코드Decentralized Arena: Towards Democratic and Scalable Automatic Evaluation of Language Models
https://github.com/mala-lab/opencil
공식 코드OpenCIL: Benchmarking Out-of-Distribution Detection in Class-Incremental Learning
https://github.com/malikmtahir/epi
공식 코드https://github.com/mandyyyyii/scibench
공식 코드SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models
https://github.com/maoyj1998/transdic
공식 코드https://github.com/marcelsheeny/radiate_sdk
공식 코드RADIATE: A Radar Dataset for Automotive Perception in Bad Weather
https://github.com/marcovirgolin/GP-GOMEA
공식 코드Contemporary Symbolic Regression Methods and their Relative Performance
https://github.com/marct0k/franck
공식 코드Fedivertex: a Graph Dataset based on Decentralized Social Networks for Trustworthy Machine Learning
https://github.com/marialaurasantoni/diversity-fitness
공식 코드Illuminating the Diversity-Fitness Trade-Off in Black-Box Optimization
https://github.com/marieoestreich/pro-gene-gen
공식 코드Towards Biologically Plausible and Private Gene Expression Data Generation
https://github.com/mariotheone/gretel
공식 코드https://github.com/markus93/fit-on-the-test
공식 코드On the Usefulness of the Fit-on-the-Test View on Evaluating Calibration of Classifiers
https://github.com/marrlab/domainlab
공식 코드DomainLab: A modular Python package for domain generalization in deep learning
https://github.com/marsggbo/CovidNet3D
공식 코드https://github.com/martinbeseda/steady-state
공식 코드A Kernel-Based Approach for Accurate Steady-State Detection in Performance Time Series
https://github.com/martinjurkovic/syntherela
공식 코드Benchmarking the Fidelity and Utility of Synthetic Relational Data
https://github.com/martinmenten/skeletonization-for-gradient-based-optimization
공식 코드https://github.com/martinzaefferer/COBBS
공식 코드https://github.com/martinzaefferer/zaef20b
공식 코드https://github.com/marvinlvn/babyslm
공식 코드BabySLM: language-acquisition-friendly benchmark of self-supervised spoken language models
https://github.com/mary-paterson/laryngealcancerclassificationbenchmark
공식 코드https://github.com/maryammaryam877/genai_tigs
공식 코드Benchmarking Generative AI Models for Deep Learning Test Input Generation
https://github.com/mateoespinosa/concept-quality
공식 코드Towards Robust Metrics for Concept Representation Evaluation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.