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BIG-bench Machine Learning

This branch include most common machine learning fundamental algorithms.

Papers

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Showing 2276–2300 of 10033 papers

TitleStatusHype
Invertible Surrogate Models: Joint surrogate modelling and reconstruction of Laser-Wakefield Acceleration by invertible neural networks—0
A survey of machine learning-based physics event generation—0
Decision Concept Lattice vs. Decision Trees and Random Forests—0
Markpainting: Adversarial Machine Learning meets InpaintingCode1
Duckworth-Lewis-Stern Method Comparison with Machine Learning Approach—0
Understanding peacefulness through the world newsCode0
Know Your Model (KYM): Increasing Trust in AI and Machine Learning—0
Machine-Learning Non-Conservative Dynamics for New-Physics Detection—0
Using Pareto Simulated Annealing to Address Algorithmic Bias in Machine Learning—0
Generalized AdaGrad (G-AdaGrad) and Adam: A State-Space Perspective—0
Product Progression: a machine learning approach to forecasting industrial upgrading—0
A Simple and General Debiased Machine Learning Theorem with Finite Sample Guarantees—0
Machine Learning for Security in Vehicular Networks: A Comprehensive Survey—0
Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methods—0
Transfer Learning as an Enhancement for Reconfiguration Management of Cyber-Physical Production Systems—0
A remark on a paper of Krotov and Hopfield [arXiv:2008.06996]—0
Gradient-based Data Subversion Attack Against Binary Classifiers—0
Characterization of Generalizability of Spike Timing Dependent Plasticity trained Spiking Neural Networks—0
Quantum Federated Learning with Quantum DataCode1
Evaluating Resilience of Encrypted Traffic Classification Against Adversarial Evasion Attacks—0
Analysis and classification of main risk factors causing stroke in Shanxi Province—0
Ten Quick Tips for Deep Learning in BiologyCode1
Fit without fear: remarkable mathematical phenomena of deep learning through the prism of interpolationCode1
Estimating air quality co-benefits of energy transition using machine learning—0
Machine Learning for Performance Prediction of Channel Bonding in Next-Generation IEEE 802.11 WLANs—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Fb232account and password 100—Unverified