Papers with Code 아카이브

Holdout Set

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

1

보존된 평가 기록

5

코드

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

https://github.com/aangelopoulos/rcps

공식 코드

Distribution-Free, Risk-Controlling Prediction Sets

https://github.com/acmi-lab/ratt_generalization_bound

공식 코드

RATT: Leveraging Unlabeled Data to Guarantee Generalization

https://github.com/alibaba-damo-academy/pixel-lesion-patient-network

공식 코드

Liver Tumor Screening and Diagnosis in CT with Pixel-Lesion-Patient Network

https://github.com/asier-gutierrez/nn-evolution

공식 코드

Persistent Homology Captures the Generalization of Neural Networks Without A Validation Set

https://github.com/deepmind/dm_memorytasks

공식 코드

Generalization of Reinforcement Learners with Working and Episodic Memory

https://github.com/derEitel/explainableMS

공식 코드

Uncovering convolutional neural network decisions for diagnosing multiple sclerosis on conventional MRI using layer-wise relevance propagation

https://github.com/diux-xview/xview3-reference

공식 코드

xView3-SAR: Detecting Dark Fishing Activity Using Synthetic Aperture Radar Imagery

https://github.com/drsleep/nas-segm-pytorch

공식 코드

Template-Based Automatic Search of Compact Semantic Segmentation Architectures

https://github.com/dsurian/matfac

공식 코드

A shared latent space matrix factorisation method for recommending new trial evidence for systematic review updates

https://github.com/enscma2/fairest-mixup

공식 코드

Who's the (Multi-)Fairest of Them All: Rethinking Interpolation-Based Data Augmentation Through the Lens of Multicalibration

https://github.com/google-deepmind/transformer_ngrams

공식 코드

Understanding Transformers via N-gram Statistics

https://github.com/jamesliley/optholdoutsize_pipelines

공식 코드

Holdouts set for safe predictive model updating

https://github.com/ml-stat-Sustech/Parametric-Scaling-Law-CP-Tuning

공식 코드

Parametric Scaling Law of Tuning Bias in Conformal Prediction

https://github.com/robert-graf/totalvibesegmentator

공식 코드

TotalVibeSegmentator: Full Body MRI Segmentation for the NAKO and UK Biobank

https://github.com/schmidttgenstein/qudost

공식 코드

Testing for Overfitting

https://github.com/DIDSR/ThresholdoutAUC

Generalization in Adaptive Data Analysis and Holdout Reuse

https://github.com/adamzenith/mapie

Distribution-Free, Risk-Controlling Prediction Sets

https://github.com/scikit-learn-contrib/mapie

Distribution-Free, Risk-Controlling Prediction Sets

https://github.com/zhaoolee/garss

Understanding Transformers via N-gram Statistics

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