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

arXiv: https://arxiv.org/abs/2205.03373 · HTML: https://mlsanity.com/paper/2205.03373/

## Key facts

- Cited by 22 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 50 references that are in the map.
- First posted on arXiv 4 May 2022.

## Builds on (most cited first, 8 of 8)

- [Intrinsic dimension of data representations in deep neural networks](https://mlsanity.com/paper/1905.12784/) (2019)
- [Estimating the intrinsic dimension of datasets by a minimal neighborhood information](https://mlsanity.com/paper/1803.06992/) (2018)
- [Hierarchical nucleation in deep neural networks](https://mlsanity.com/paper/2007.03506/) (2020)
- [Ranking the information content of distance measures](https://mlsanity.com/paper/2104.15079/) (2021)
- [Automatic topography of high-dimensional data sets by non-parametric Density Peak clustering](https://mlsanity.com/paper/1802.10549/) (2018)
- [Unfolding Hidden Barriers by Active Enhanced Sampling](https://mlsanity.com/paper/1705.07414/) (2017)
- [Distributional Results for Model-Based Intrinsic Dimension Estimators](https://mlsanity.com/paper/2104.13832/) (2021)
- [Dynamical Landscape and Multistability of a Climate Model](https://mlsanity.com/paper/2010.10374/) (2020)

## Built on by (most cited first, 22 of 22)

- [The geometry of hidden representations of large transformer models](https://mlsanity.com/paper/2302.00294/) (2023)
- [EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling](https://mlsanity.com/paper/2502.09509/) (2025)
- [Latent Thinking Optimization: Your Latent Reasoning Language Model Secretly Encodes Reward Signals in Its Latent Thoughts](https://mlsanity.com/paper/2509.26314/) (2025)
- [CryoBench: Diverse and challenging datasets for the heterogeneity problem in cryo-EM](https://mlsanity.com/paper/2408.05526/) (2024)
- [The representation landscape of few-shot learning and fine-tuning in large language models](https://mlsanity.com/paper/2409.03662/) (2024)
- [Unlocking Pretrained Vision Transformers for Time Series Classification](https://mlsanity.com/paper/2506.08641/) (2025)
- [Automatic feature selection and weighting in molecular systems using Differentiable Information Imbalance](https://mlsanity.com/paper/2411.00851/) (2024)
- [FSVideo: Fast Speed Video Diffusion Model in a Highly-Compressed Latent Space](https://mlsanity.com/paper/2602.02092/) (2026)
- [Intrinsic dimension estimation for discrete metrics](https://mlsanity.com/paper/2207.09688/) (2022)
- [Scale adaptive and robust intrinsic dimension estimation via optimal neighbourhood identification](https://mlsanity.com/paper/2405.15132/) (2024)
- [LF2AR: Accounting for Layerwise Dynamics to Improve Multimodal Adaptation of Language Models](https://mlsanity.com/paper/2503.06211/) (2025)
- [Unsupervised detection of semantic correlations in big data](https://mlsanity.com/paper/2411.02126/) (2024)
- [Understanding Variational Autoencoders with Intrinsic Dimension and Information Imbalance](https://mlsanity.com/paper/2411.01978/) (2024)
- [Detecting Localized Density Anomalies in Multivariate Data via Coin-Flip Statistics](https://mlsanity.com/paper/2503.23927/) (2025)
- [Quantifying Manifolds: Do the manifolds learned by Generative Adversarial Networks converge to the real data manifold](https://mlsanity.com/paper/2403.05033/) (2024)
- [Density Estimation via Binless Multidimensional Integration](https://mlsanity.com/paper/2407.08094/) (2024)
- [When fractional quasi p-norms concentrate](https://mlsanity.com/paper/2505.19635/) (2025)
- [Coupled reaction and diffusion governing interface evolution in solid-state batteries](https://mlsanity.com/paper/2506.10944/) (2025)
- [Rethinking Intrinsic Dimension Estimation in Neural Representations](https://mlsanity.com/paper/2604.20276/) (2026)
- [Texture Representations in Deep Vision Models: Comparing CNNs, Vision Transformers, and Human Perception](https://mlsanity.com/paper/2607.08321/) (2026)
- [Local and Global Regimes of Geometric Complexity in Language Model Representations](https://mlsanity.com/paper/2608.14361/) (2026)
- [Psychosis involves a deficit of information compression in connected speech](https://mlsanity.com/paper/2609.15522/) (2026)

## 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.