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BIG-bench Machine Learning

This branch include most common machine learning fundamental algorithms.

Papers

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Showing 1–50 of 10033 papers

TitleStatusHype
Synthetic Dataset Generation for Adversarial Machine Learning ResearchCode6
TensorIR: An Abstraction for Automatic Tensorized Program OptimizationCode6
Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and ValuesCode5
Flashlight: Enabling Innovation in Tools for Machine LearningCode5
Pen and Paper Exercises in Machine LearningCode4
Deepchecks: A Library for Testing and Validating Machine Learning Models and DataCode4
GPUTreeShap: Massively Parallel Exact Calculation of SHAP Scores for Tree EnsemblesCode4
XGBoost: A Scalable Tree Boosting SystemCode4
DeepCAVE: An Interactive Analysis Tool for Automated Machine LearningCode3
Sintel: A Machine Learning Framework to Extract Insights from SignalsCode3
TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug DiscoveryCode3
Declarative Machine Learning SystemsCode3
River: machine learning for streaming data in PythonCode3
Auto-Sklearn 2.0: Hands-free AutoML via Meta-LearningCode3
Feature Selection Methods for Uplift Modeling and Heterogeneous Treatment EffectCode3
YOLOv4: Optimal Speed and Accuracy of Object DetectionCode3
CausalML: Python Package for Causal Machine LearningCode3
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligenceCode3
SQLFlow: A Bridge between SQL and Machine LearningCode3
pyannote.audio: neural building blocks for speaker diarizationCode3
InterpretML: A Unified Framework for Machine Learning InterpretabilityCode3
MMLSpark: Unifying Machine Learning Ecosystems at Massive ScalesCode3
Benchmarking Automatic Machine Learning FrameworksCode3
Adversarial Robustness Toolbox v1.0.0Code3
mlpack 3: a fast, flexible machine learning libraryCode3
Layered TPOT: Speeding up Tree-based Pipeline OptimizationCode3
Performance Analysis of Open Source Machine Learning Frameworks for Various Parameters in Single-Threaded and Multi-Threaded ModesCode3
Designing and building the mlpack open-source machine learning libraryCode3
Efficient and Robust Automated Machine LearningCode3
Supplementary Material for Efficient and Robust Automated Machine LearningCode3
Deep Reinforcement Learning for Multi-Agent InteractionCode2
EC-KitY: Evolutionary Computation Tool Kit in Python with Seamless Machine Learning IntegrationCode2
HierarchicalForecast: A Reference Framework for Hierarchical Forecasting in PythonCode2
Learning to correct spectral methods for simulating turbulent flowsCode2
Torsional Diffusion for Molecular Conformer GenerationCode2
MACE: An Efficient Model-Agnostic Framework for Counterfactual ExplanationCode2
Satellite Image Time Series Analysis for Big Earth Observation DataCode2
auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event DataCode2
Implementation of an Automated Learning System for Non-expertsCode2
Graph Data Augmentation for Graph Machine Learning: A SurveyCode2
An Introduction to Neural Data CompressionCode2
OMLT: Optimization & Machine Learning ToolkitCode2
ERS: a novel comprehensive endoscopy image dataset for machine learning, compliant with the MST 3.0 specificationCode2
Uncertainty Quantification in Scientific Machine Learning: Methods, Metrics, and ComparisonsCode2
Scaling Language Models: Methods, Analysis & Insights from Training GopherCode2
Designing Inherently Interpretable Machine Learning ModelsCode2
TorchAudio: Building Blocks for Audio and Speech ProcessingCode2
Tribuo: Machine Learning with Provenance in JavaCode2
Scale-invariant Learning by Physics InversionCode2
Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty QuantificationCode2
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Benchmark Results

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1Fb232account and password 100—Unverified