SOTAVerified

BIG-bench Machine Learning

This branch include most common machine learning fundamental algorithms.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2826–2850 of 10033 papers

TitleStatusHype
Autocalibration and Tweedie-dominance for Insurance Pricing with Machine LearningCode0
Efficient Encrypted Inference on Ensembles of Decision Trees—0
Eigen-spectrograms: An interpretable feature space for bearing fault diagnosis based on artificial intelligence and image processing—0
Training a First-Order Theorem Prover from Synthetic Data—0
A Novel Framework for Threat Analysis of Machine Learning-based Smart Healthcare Systems—0
MD-MTL: An Ensemble Med-Multi-Task Learning Package for DiseaseScores Prediction and Multi-Level Risk Factor Analysis—0
Causal Analysis of Agent Behavior for AI Safety—0
GenoML: Automated Machine Learning for Genomics—0
Quantifying identifiability to choose and audit ε in differentially private deep learningCode0
Analysing Wideband Absorbance Immittance in Normal and Ears with Otitis Media with Effusion Using Machine Learning—0
Generalization Bounds for Sparse Random Feature ExpansionsCode0
Out of Distribution Generalization in Machine LearningCode1
Malware Classification with Word Embedding Features—0
Root cause prediction based on bug reports—0
Hybrid and Automated Machine Learning Approaches for Oil Fields Development: the Case Study of Volve Field, North SeaCode1
A Multi-Modal Respiratory Disease Exacerbation Prediction Technique Based on a Spatio-Temporal Machine Learning Architecture—0
A Modified Drake Equation for Assessing Adversarial Risk to Machine Learning Models—0
Evaluation and Optimization of Distributed Machine Learning Techniques for Internet of ThingsCode1
Predicting Driver Fatigue in Automated Driving with Explainability—0
Machine Learning using Stata/Python—0
Land Cover Mapping in Limited Labels Scenario: A Survey—0
SURFBoard: Reproducible Performance Analysis for Distributed Machine Learning Workflows—0
Standing on the Shoulders of Machine Learning: Can We Improve Hypothesis Testing?Code0
An Interpretable Multiple-Instance Approach for the Detection of referable Diabetic Retinopathy from Fundus Images—0
Sibyl: Understanding and Addressing the Usability Challenges of Machine Learning In High-Stakes Decision Making—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Fb232account and password 100—Unverified