Papers with Code 아카이브

BIG-bench Machine Learning

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 0
평가표: 2
보존된 평가 기록: 2

This branch include most common machine learning fundamental algorithms.

코드

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

https://github.com/alexrenz/lapse-ps

공식 코드

Dynamic Parameter Allocation in Parameter Servers

https://github.com/algofairness/fairness-comparison

공식 코드

A comparative study of fairness-enhancing interventions in machine learning

https://github.com/allambert/torch_itl

공식 코드

Emotion Transfer Using Vector-Valued Infinite Task Learning

https://github.com/allenye66/Malware-and-Ensemble-Learning-Research

공식 코드

On Ensemble Learning

https://github.com/almomaa/ERFit-Package

공식 코드

ERFit: Entropic Regression Fit Matlab Package, for Data-Driven System Identification of Underlying Dynamic Equations

https://github.com/alxshine/foreNNsic

공식 코드

Forensicability of Deep Neural Network Inference Pipelines

https://github.com/amaiya/ktrain

공식 코드

ktrain: A Low-Code Library for Augmented Machine Learning

https://github.com/amanat9/QuantopianThesis

공식 코드

Combining Machine Learning Classifiers for Stock Trading with Effective Feature Extraction

https://github.com/amangkim/ECGRegreSec

공식 코드

An Enhanced Electrocardiogram Biometric Authentication System Using Machine Learning

https://github.com/amangkim/RRIFECGSec

공식 코드

An Enhanced Machine Learning-based Biometric Authentication System Using RR-Interval Framed Electrocardiograms

https://github.com/amangkim/amgecg_toolbox

공식 코드

A Machine Learning Framework for Biometric Authentication using Electrocardiogram

https://github.com/amartya18x/tapas

공식 코드

TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service

https://github.com/amidst/jss

공식 코드

AMIDST: a Java Toolbox for Scalable Probabilistic Machine Learning

https://github.com/aminesi/robustness-on-device

공식 코드

Robustness Analysis of Deep Learning Frameworks on Mobile Platforms

https://github.com/amiratag/DataShapley

공식 코드

Data Shapley: Equitable Valuation of Data for Machine Learning

https://github.com/amirgholami/adahessian

공식 코드

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning

https://github.com/anahideh/FAL--Fair-Active-Learning

공식 코드

Fair Active Learning

https://github.com/anandsagarthumati9848/HIDS

공식 코드

Data Curation and Quality Assurance for Machine Learning-based Cyber Intrusion Detection

https://github.com/ananyajana/interpretable_covid19

공식 코드

Global and Local Interpretation of black-box Machine Learning models to determine prognostic factors from early COVID-19 data

https://github.com/anasbair/SemEval2020-groups

공식 코드

DUTH at SemEval-2020 Task 11: BERT with Entity Mapping for Propaganda Classification

https://github.com/anavaldi/fairness_nsga

공식 코드

How fair can we go in machine learning? Assessing the boundaries of fairness in decision trees

https://github.com/andreArtelt/ConvexDensityConstraintsForPlausibleCounterfactuals

공식 코드

Convex Density Constraints for Computing Plausible Counterfactual Explanations

https://github.com/andreArtelt/OnTheComputationOfCounterfactualExplanations

공식 코드

On the computation of counterfactual explanations -- A survey

https://github.com/andreArtelt/contrastive_explanations

공식 코드

Efficient computation of contrastive explanations

https://github.com/andreArtelt/efficient_computation_counterfactuals_lvq

공식 코드

Efficient computation of counterfactual explanations of LVQ models

https://github.com/andrea08/question_answer_annotation

공식 코드

Toward Dialogue Modeling: A Semantic Annotation Scheme for Questions and Answers

https://github.com/andreartelt/diversesemifactualsreject

공식 코드

"Even if ..." -- Diverse Semifactual Explanations of Reject

https://github.com/andreasr27/LAS

공식 코드

Learning Augmented Energy Minimization via Speed Scaling

https://github.com/andreasvc/litquest

공식 코드

Results of a Single Blind Literary Taste Test with Short Anonymized Novel Fragments

https://github.com/andrewyyp/kernel-doubly-robust

공식 코드

Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference

https://github.com/andruekonst/egbm-gam

공식 코드

Interpretable Machine Learning with an Ensemble of Gradient Boosting Machines

https://github.com/anewgithubname/Trimmed-Density-Ratio-Estimation

공식 코드

Trimmed Density Ratio Estimation

https://github.com/angione-lab/12-machine-learning-models-for-text-classification

공식 코드

A pipeline and comparative study of 12 machine learning models for text classification

https://github.com/angpapadi/Visual-Representation-Decoding-from-Human-Brain-Activity

공식 코드

Decoding Generic Visual Representations From Human Brain Activity using Machine Learning

https://github.com/anirudh9784/Adversarial-Attacks-and-Defences

공식 코드

An integrated Auto Encoder-Block Switching defense approach to prevent adversarial attacks

https://github.com/anish-lakkapragada/ActivRecognition-Autism-Diagnosis

공식 코드

Classification of Abnormal Hand Movement for Aiding in Autism Detection: Machine Learning Study

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