Publications by Adám Gosztolai

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Describing networks geometrically through low-dimensional latent metric spaces has helped design efficient learning algorithms, unveil network symmetries and study dynamical network processes. However, latent space embeddings are limited to specific classe ...

A major goal shared by neuroscience and collective behavior is to understand how dynamic interactions between individual elements give rise to behaviors in populations of neurons and animals, respectively. This goal has recently become within reach, thanks ...

LiftPose3D infers three-dimensional poses from two-dimensional data or from limited three-dimensional data. The approach is illustrated for videos of behaving Drosophila, mice, rats and macaques. ...

We present PyGenStability, a general-use Python software package that provides a suite of analysis and visualization tools for unsupervised multiscale community detection in graphs. PyGenStability finds optimized partitions of a graph at different levels o ...

The response of microbes to external signals is mediated by biochemical networks with intrinsic time scales. These time scales give rise to a memory that impacts cellular behaviour. Here we study theoretically the role of cellular memory in Escherichia col ...

Adám Gosztolai

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Unfolding the multiscale structure of networks with dynamical Ollivier-Ricci curvature

Connecting the dots in ethology: applying network theory to understand neural and animal collectives

LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals

Algorithm 1044: PyGenStability, a Multiscale Community Detection with Generalized Markov Stability

Interpreting and comparing neural activity across systems by geometric deep learning

Cellular memory enhances bacterial chemotactic navigation in rugged environments