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BIG-bench Machine Learning

This branch include most common machine learning fundamental algorithms.

Papers

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Showing 526–550 of 10033 papers

TitleStatusHype
A Preliminary Study of Neural Network-based Approximation for HPC ApplicationsCode1
A quantum algorithm for training wide and deep classical neural networksCode1
Approximate Network Motif Mining Via Graph LearningCode1
70 years of machine learning in geoscience in reviewCode1
Approximating Network Centrality Measures Using Node Embedding and Machine LearningCode1
A Rationale-Centric Framework for Human-in-the-loop Machine LearningCode1
A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph PerspectiveCode1
A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine LearningCode1
Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation ApproachesCode1
A simple equivariant machine learning method for dynamics based on scalarsCode1
A smile is all you need: Predicting limiting activity coefficients from SMILES with natural language processingCode1
A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data SetCode1
A Survey of Label-noise Representation Learning: Past, Present and FutureCode1
A survey on datasets for fairness-aware machine learningCode1
A Survey on Machine Learning Algorithms for Applications in Cognitive Radio NetworksCode1
Attacks on Image Encryption Schemes for Privacy-Preserving Deep Neural NetworksCode1
AIPerf: Automated machine learning as an AI-HPC benchmarkCode1
AugLiChem: Data Augmentation Library of Chemical Structures for Machine LearningCode1
Augmented Ultrasonic Data for Machine LearningCode1
A Unified View of Relational Deep Learning for Drug Pair ScoringCode1
AutoCLINT: The Winning Method in AutoCV Challenge 2019Code1
AutoKE: An automatic knowledge embedding framework for scientific machine learningCode1
Auto-KWS 2021 Challenge: Task, Datasets, and BaselinesCode1
Automated Evolutionary Approach for the Design of Composite Machine Learning PipelinesCode1
A Novel Framework for Spatio-Temporal Prediction of Environmental Data Using Deep LearningCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Fb232account and password 100—Unverified