Alternatives and similar repositories for EvOAutoML:

Users that are interested in EvOAutoML are comparing it to the libraries listed below

• online-ml / deep-river
  ☆134Updated 2 weeks ago
• JHoelli / TSEvo
  "TSEvo: Counterfactuals for Time Series Classification" accepted at ICMLA '22.
  ☆14Updated 2 years ago
• haugjo / float
  A modular Python framework for standardized evaluation and benchmarking of online learning models.
  ☆9Updated 2 years ago
• mmschlk / iXAI
  Fast and incremental explanations for online machine learning models. Works best with the river framework.
  ☆54Updated 3 months ago
• machinelearningnuremberg / DeepRankingEnsembles
  [ICLR 2023] Deep Ranking Ensembles for Hyperparameter Optimization
  ☆14Updated last year
• sebastianpinedaar / MMAML-TSR
  Multi-modal meta-learning for time series regression
  ☆26Updated 10 months ago
• machinelearningnuremberg / DyHPO
  [NeurIPS 2022] Supervising the Multi-Fidelity Race of Hyperparameter Configurations
  ☆12Updated 2 years ago
• soda-inria / tabicl
  Repository for TabICL: A Tabular Foundation Model for In-Context Learning on Large Data
  ☆37Updated last month
• automl / ifBO
  In-context Bayesian Optimization
  ☆16Updated 3 months ago
• machinelearningnuremberg / FSBO
  [ICLR 2021] Few Shot Bayesian Optimization
  ☆19Updated 2 years ago
• yandex-research / tabred
  TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks
  ☆69Updated 3 weeks ago
• hoanganhngo610 / river-clustering-demo-2022
  This repository serves as a demo for River and its associated clustering module (2022 edition).
  ☆13Updated last year
• ealcobaca / pymfe
  Python Meta-Feature Extractor package.
  ☆133Updated 10 months ago
• machinelearningnuremberg / QuickTune
  [ICLR2024] Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
  ☆32Updated 5 months ago
• peaclab / CoMTE
  Counterfactual Explanations for Multivariate Time Series Data
  ☆31Updated last year
• mitre / menelaus
  Online and batch-based concept and data drift detection algorithms to monitor and maintain ML performance.
  ☆67Updated last year
• automl / lcpfn
  ☆16Updated 6 months ago
• machinelearningnuremberg / DeepPipe
  [KDD 2023] Deep Pipeline Embeddings for AutoML
  ☆16Updated 5 months ago
• automl / neps
  Neural Pipeline Search (NePS): Helps deep learning experts find the best neural pipeline.
  ☆72Updated last week
• alipsgh / data-streams
  You will find (about) synthetic and real-world data streams in this repository.
  ☆47Updated 4 years ago
• machinelearningnuremberg / WellTunedSimpleNets
  [NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets
  ☆85Updated 2 years ago
• automl / quicktunetool
  A framework for QuickTune
  ☆16Updated 3 months ago
• songqiaohu / THU-Concept-Drift-Datasets-v1.0
  📖These are the concept drift datasets we made, and we open-source the data and corresponding interfaces. Welcome to use them for free if…
  ☆30Updated last year
• automl / DeepCAVE
  An interactive framework to visualize and analyze your AutoML process in real-time.
  ☆87Updated last week
• tornede / py_experimenter
  The PyExperimenter is a tool for the automatic execution of experiments, e.g. for machine learning (ML), capturing corresponding results …
  ☆35Updated 2 months ago
• automl / PFNs4BO
  The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization
  ☆26Updated last year
• machinelearningnuremberg / DPL
  [NeurIPS 2023] Multi-fidelity hyperparameter optimization with deep power laws that achieves state-of-the-art results across diverse benc…
  ☆15Updated last year
• automl / PFNs
  Our maintained PFN repository. Come here to train SOTA PFNs.
  ☆78Updated last week
• TimeEval / GutenTAG
  GutenTAG is an extensible tool to generate time series datasets with and without anomalies; integrated with TimeEval.
  ☆82Updated 2 months ago
• JHoelli / Awesome-Time-Series-Explainability
  A list of (post-hoc) XAI for time series
  ☆130Updated 7 months ago