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BIG-bench Machine Learning

This branch include most common machine learning fundamental algorithms.

Papers

Showing 2650 of 10033 papers

TitleStatusHype
mlpack 3: a fast, flexible machine learning libraryCode3
InterpretML: A Unified Framework for Machine Learning InterpretabilityCode3
Performance Analysis of Open Source Machine Learning Frameworks for Various Parameters in Single-Threaded and Multi-Threaded ModesCode3
Supplementary Material for Efficient and Robust Automated Machine LearningCode3
Layered TPOT: Speeding up Tree-based Pipeline OptimizationCode3
ktrain: A Low-Code Library for Augmented Machine LearningCode2
Learning to correct spectral methods for simulating turbulent flowsCode2
Instead of Rewriting Foreign Code for Machine Learning, Automatically Synthesize Fast GradientsCode2
MACE: An Efficient Model-Agnostic Framework for Counterfactual ExplanationCode2
HierarchicalForecast: A Reference Framework for Hierarchical Forecasting in PythonCode2
Graph Data Augmentation for Graph Machine Learning: A SurveyCode2
hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning DevicesCode2
Geomstats: A Python Package for Riemannian Geometry in Machine LearningCode2
Foolbox: A Python toolbox to benchmark the robustness of machine learning modelsCode2
Fused Gromov-Wasserstein distance for structured objects: theoretical foundations and mathematical propertiesCode2
Implementation of an Automated Learning System for Non-expertsCode2
Machine Learning in Asset Management—Part 1: Portfolio Construction—Trading StrategiesCode2
Explaining Machine Learning Classifiers through Diverse Counterfactual ExplanationsCode2
ERS: a novel comprehensive endoscopy image dataset for machine learning, compliant with the MST 3.0 specificationCode2
Towards Backdoor Attacks and Defense in Robust Machine Learning ModelsCode2
Advbox: a toolbox to generate adversarial examples that fool neural networksCode2
Fast inference of deep neural networks in FPGAs for particle physicsCode2
Designing Inherently Interpretable Machine Learning ModelsCode2
geomstats: a Python Package for Riemannian Geometry in Machine LearningCode2
Advances and Open Problems in Federated LearningCode2
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Benchmark Results

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