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05/18/2023
Robust inference of causality in high-dimensional dynamical processes from the Information Imbalance of distance ranks
We introduce an approach which allows inferring causal relationships bet...
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04/14/2023
Optimal inference of a generalised Potts model by single-layer transformers with factored attention
Transformers are the type of neural networks that has revolutionised nat...
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03/02/2023
Optimal transfer protocol by incremental layer defrosting
Transfer learning is a powerful tool enabling model training with limite...
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02/01/2023
The geometry of hidden representations of large transformer models
Large transformers are powerful architectures for self-supervised analys...
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07/20/2022
Intrinsic dimension estimation for discrete metrics
Real world-datasets characterized by discrete features are ubiquitous: f...
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05/27/2022
Prune and distill: similar reformatting of image information along rat visual cortex and deep neural networks
Visual object recognition has been extensively studied in both neuroscie...
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05/04/2022
DADApy: Distance-based Analysis of DAta-manifolds in Python
DADApy is a python software package for analysing and characterising hig...
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06/07/2021
Representation mitosis in wide neural networks
Deep neural networks (DNNs) defy the classical bias-variance trade-off: ...
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04/30/2021
Ranking the information content of distance measures
Real-world data typically contain a large number of features that are of...
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04/28/2021
Distributional Results for Model-Based Intrinsic Dimension Estimators
Modern datasets are characterized by a large number of features that may...
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10/20/2020
Dynamical Landscape and Multistability of the Earth's Climate
We apply two independent data analysis methodologies to locate stable cl...
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07/07/2020
Hierarchical nucleation in deep neural networks
Deep convolutional networks (DCNs) learn meaningful representations wher...
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05/29/2019
Intrinsic dimension of data representations in deep neural networks
Deep neural networks progressively transform their inputs across multipl...
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02/27/2019
Clustering by the local intrinsic dimension: the hidden structure of real-world data
It is well known that a small number of variables is often sufficient to...
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03/19/2018
Estimating the intrinsic dimension of datasets by a minimal neighborhood information
Analyzing large volumes of high-dimensional data is an issue of fundamen...
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02/28/2018
