SOTAVerified

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

Showing 1–10 of 641 papers

TitleStatusHype
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe SystemsCode7
TabRepo: A Large Scale Repository of Tabular Model Evaluations and its AutoML ApplicationsCode6
AutoGluon-TimeSeries: AutoML for Probabilistic Time Series ForecastingCode6
MOSPAT: AutoML based Model Selection and Parameter Tuning for Time Series Anomaly DetectionCode5
MobileVLM V2: Faster and Stronger Baseline for Vision Language ModelCode5
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a SecondCode5
BigDL 2.0: Seamless Scaling of AI Pipelines from Laptops to Distributed ClusterCode5
Efficient Automated Deep Learning for Time Series ForecastingCode4
Open Problems in Applied Deep LearningCode4
AutoGluon-Tabular: Robust and Accurate AutoML for Structured DataCode3
Show:102550
← PrevPage 1 of 65Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1marc.boulleRank (AutoML5)6.4—Unverified
2reference_mbRank (AutoML5)5.2—Unverified
3postech.mlg_exbrainRank (AutoML5)5.2—Unverified
4abhishek4Rank (AutoML5)4.6—Unverified
5referenceRank (AutoML5)4.4—Unverified
6reference_lsRank (AutoML5)4—Unverified
7djajeticRank (AutoML5)3—Unverified
8aad_freiburgRank (AutoML5)1.6—Unverified
#ModelMetricClaimedVerifiedStatus
1Logistic RegressionAccuracy97.02—Unverified
#ModelMetricClaimedVerifiedStatus
1Zero-shot-BERT-SORT1:1 Accuracy55—Unverified
#ModelMetricClaimedVerifiedStatus
1Logistic Regressionaccuracy98.33—Unverified