AutoML

Automated Machine Learning (AutoML) is a general concept which covers diverse techniques for automated model learning including automatic data preprocessing, architecture search, and model selection. Source: Evaluating recommender systems for AI-driven data science (1905.09205)

Source: CHOPT : Automated Hyperparameter Optimization Framework for Cloud-Based Machine Learning Platforms

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1–25 of 641 papers

Title	Date	Tasks	Status	Hype
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems	Mar 31, 2025	AutoMLContinual Learning	CodeCode Available	7
TabRepo: A Large Scale Repository of Tabular Model Evaluations and its AutoML Applications	Nov 6, 2023	AutoMLHyperparameter Optimization	CodeCode Available	6
AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting	Aug 10, 2023	AutoMLPhilosophy	CodeCode Available	6
MobileVLM V2: Faster and Stronger Baseline for Vision Language Model	Feb 6, 2024	AutoMLLanguage Modeling	CodeCode Available	5
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second	Jul 5, 2022	AutoMLBayesian Inference	CodeCode Available	5
MOSPAT: AutoML based Model Selection and Parameter Tuning for Time Series Anomaly Detection	May 24, 2022	Anomaly DetectionAutoML	CodeCode Available	5
BigDL 2.0: Seamless Scaling of AI Pipelines from Laptops to Distributed Cluster	Apr 3, 2022	AutoMLDistributed Computing	CodeCode Available	5
Open Problems in Applied Deep Learning	Jan 26, 2023	AutoMLDeep Learning	CodeCode Available	4
Efficient Automated Deep Learning for Time Series Forecasting	May 11, 2022	AutoMLBayesian Optimization	CodeCode Available	4
MLZero: A Multi-Agent System for End-to-end Machine Learning Automation	May 20, 2025	AutoMLCode Generation	CodeCode Available	3
MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices	Dec 28, 2023	AutoMLCPU	CodeCode Available	3
DeepCAVE: An Interactive Analysis Tool for Automated Machine Learning	Jun 7, 2022	AutoMLBIG-bench Machine Learning	CodeCode Available	3
Benchmarking Multimodal AutoML for Tabular Data with Text Fields	Nov 4, 2021	AutoMLBenchmarking	CodeCode Available	3
EfficientNetV2: Smaller Models and Faster Training	Apr 1, 2021	AutoMLClassification	CodeCode Available	3
AlphaEvolve: A Learning Framework to Discover Novel Alphas in Quantitative Investment	Mar 30, 2021	AutoMLStock Prediction	CodeCode Available	3
Robust and Accurate Object Detection via Adversarial Learning	Mar 23, 2021	AutoMLData Augmentation	CodeCode Available	3
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning	Jul 8, 2020	AutoMLBIG-bench Machine Learning	CodeCode Available	3
Is deep learning necessary for simple classification tasks?	Jun 11, 2020	AutoMLBinary Classification	CodeCode Available	3
Model-based Asynchronous Hyperparameter and Neural Architecture Search	Mar 24, 2020	AutoMLBayesian Optimization	CodeCode Available	3
AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data	Mar 13, 2020	AutoMLMolecular Property Prediction	CodeCode Available	3
EfficientDet: Scalable and Efficient Object Detection	Nov 20, 2019	AutoMLObject	CodeCode Available	3
Benchmarking Automatic Machine Learning Frameworks	Aug 17, 2018	Automated Feature EngineeringAutoML	CodeCode Available	3
Layered TPOT: Speeding up Tree-based Pipeline Optimization	Jan 18, 2018	Automated Feature EngineeringAutoML	CodeCode Available	3
Efficient and Robust Automated Machine Learning	Dec 1, 2015	AutoMLBayesian Optimization	CodeCode Available	3
From Tiny Machine Learning to Tiny Deep Learning: A Survey	Jun 21, 2025	AutoMLModel Optimization	CodeCode Available	2

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All datasets Chalearn-AutoML-1 Breast Cancer Coimbra Data Set OrdinalDataset Wine

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	marc.boulle	Rank (AutoML5)	6.4	—	Unverified
2	reference_mb	Rank (AutoML5)	5.2	—	Unverified
3	postech.mlg_exbrain	Rank (AutoML5)	5.2	—	Unverified
4	abhishek4	Rank (AutoML5)	4.6	—	Unverified
5	reference	Rank (AutoML5)	4.4	—	Unverified
6	reference_ls	Rank (AutoML5)	4	—	Unverified
7	djajetic	Rank (AutoML5)	3	—	Unverified
8	aad_freiburg	Rank (AutoML5)	1.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Logistic Regression	Accuracy	97.02	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Zero-shot-BERT-SORT	1:1 Accuracy	55	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Logistic Regression	accuracy	98.33	—	Unverified