mlsanityData to 7 Oct 2026

DADApy: Distance-based Analysis of DAta-manifolds in Python

arXiv 2205.03373 ↗First posted 4 May 2022cs.LG physics.comp-ph stat.MLcited by 22

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Abstract (arXiv)

DADApy is a python software package for analysing and characterising high-dimensional data manifolds. It provides methods for estimating the intrinsic dimension and the probability density, for performing density-based clustering and for comparing different distance metrics. We review the main functionalities of the package and exemplify its usage in toy cases and in a real-world application. DADApy is freely available under the open-source Apache 2.0 license.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). Builds on 8 of its 50 references that are in the map. First posted on arXiv 4 May 2022.

Builds on

8 of 50 references.

References · 8

  1. 2019Intrinsic dimension of data representations in deep neural networkscited by 276
  2. 2018Estimating the intrinsic dimension of datasets by a minimal neighborhood informationcited by 246
  3. 2020Hierarchical nucleation in deep neural networkscited by 31
  4. 2021Ranking the information content of distance measurescited by 22
  5. 2018Automatic topography of high-dimensional data sets by non-parametric Density Peak clusteringcited by 15
  6. 2017Unfolding Hidden Barriers by Active Enhanced Samplingcited by 6
  7. 2021Distributional Results for Model-Based Intrinsic Dimension Estimatorscited by 5
  8. 2020Dynamical Landscape and Multistability of a Climate Modelcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 1; 2024: 8; 2025: 7; 2026: 5.

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  2. 2025EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modelingcited by 85
  3. 2025Latent Thinking Optimization: Your Latent Reasoning Language Model Secretly Encodes Reward Signals in Its Latent Thoughtscited by 18
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  5. 2024The representation landscape of few-shot learning and fine-tuning in large language modelscited by 14
  6. 2025Unlocking Pretrained Vision Transformers for Time Series Classificationcited by 6
  7. 2026FSVideo: Fast Speed Video Diffusion Model in a Highly-Compressed Latent Spacecited by 5
  8. 2022Intrinsic dimension estimation for discrete metricscited by 4
  9. 2024Automatic feature selection and weighting in molecular systems using Differentiable Information Imbalancecited by 4
  10. 2024Scale adaptive and robust intrinsic dimension estimation via optimal neighbourhood identificationcited by 3
  11. 2025LF2AR: Accounting for Layerwise Dynamics to Improve Multimodal Adaptation of Language Modelscited by 3
  12. 2024Unsupervised detection of semantic correlations in big datacited by 2
10 more
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  2. 2025Detecting Localized Density Anomalies in Multivariate Data via Coin-Flip Statisticscited by 1
  3. 2024Quantifying Manifolds: Do the manifolds learned by Generative Adversarial Networks converge to the real data manifoldcited by 0
  4. 2024Density Estimation via Binless Multidimensional Integrationcited by 0
  5. 2025When fractional quasi p-norms concentratecited by 0
  6. 2025Coupled reaction and diffusion governing interface evolution in solid-state batteriescited by 0
  7. 2026Rethinking Intrinsic Dimension Estimation in Neural Representationscited by 0
  8. 2026Texture Representations in Deep Vision Models: Comparing CNNs, Vision Transformers, and Human Perceptioncited by 0
  9. 2026Local and Global Regimes of Geometric Complexity in Language Model Representationscited by 0
  10. 2026Psychosis involves a deficit of information compression in connected speechcited by 0