Publications by Benjamin Ricaud

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An emerging way to deal with high-dimensional non-euclidean data is to assume that the underlying structure can be captured by a graph. Recently, ideas have begun to emerge related to the analysis of time-varying graph signals. This work aims to elevate th ...

The study of brain dynamics enables us to characterize the time-varying functional connectivity among distinct neural groups. However, current methods suffer from the absence of structural connectivity information. We propose to integrate infra-slow neural ...

One of the key challenges in the area of signal processing on graphs is to design dictionaries and transform methods to identify and exploit structure in signals on weighted graphs. To do so, we need to account for the intrinsic geometric structure of the ...

The legacy of Joseph Fourier in science is vast, especially thanks to the essential tool that the Fourier transform is. The flexibility of this analysis, its computational efficiency and the physical interpretation it offers makes it a cornerstone in many ...

Gabor analysis is one of the most common instances of time-frequency signal analysis. Choosing a suitable window for the Gabor transform of a signal is often a challenge for practical applications, in particular in audio signal processing. Many time-freque ...

Generalized versions of the entropic (Hirschman-Beckner) and support (Elad-Bruckstein) uncertainty principle are presented for frames representations. Moreover, a sharpened version of the support inequality is obtained by introducing a generalization of th ...

This paper is the first one in a series of two articles in which we revisit the optical properties of single-walled carbon nanotubes (SWNTs). Produced by rolling up a graphene sheet, SWNTs owe their intriguing properties to their cylindrical quasi-one-dime ...

Graphs are now ubiquitous in almost every field of research. Recently, new research areas devoted to the analysis of graphs and data associated to their vertices have emerged. Focusing on dynamical processes, we propose a fast, robust and scalable framewor ...

In this work, we propose a new, fast and scalable method for anomaly detection in large time-evolving graphs. It may be a static graph with dynamic node attributes (e.g. time-series), or a graph evolving in time, such as a temporal network. We define an an ...

Graph Signal Processing generalizes classical signal processing to signal or data indexed by the vertices of a weighted graph. So far, the research efforts have been focused on static graph signals. However numerous applications involve graph signals evolv ...

A method to extract patterns of activity from time series of data structured as a network of objects, the method comprising the steps of creating a base graph of similar or related items from a given corpus by comparing intrinsic features of the items, com ...

Visual short-term memory binding tasks are a promising early marker for Alzheimer's disease (AD). To uncover functional deficits of AD in these tasks it is meaningful to first study unimpaired brain function. Electroencephalogram recordings were obtained f ...

A number of new localized, multiscale transforms have recently been introduced to analyze data residing on weighted graphs. In signal processing tasks such as regularization and compression, much of the power of classical wavelets on the real line is deriv ...

We investigate the design of a convolutional layer where kernels are parameterized functions. This layer aims at being the input layer of convolutional neural networks for audio applications or applications involving time-series. The kernels are defined as ...

This article provides feedback on a multidisciplinary and applied research project to design a data mapping and exploration tool on Twitter for journalists. The approach focuses on the observation and understanding of journalists' uses and a projection of ...

The goal of this paper is to review the main trends in the domain of uncertainty principles and localization, highlight their mutual connections and investigate practical consequences. The discussion is strongly oriented towards, and motivated by signal pr ...

In this work, we propose an automatic evaluation and comparison of the browsing behavior of Wikipedia readers that can be applied to any language editions of Wikipedia. As an example, we focus on English, French, and Russian languages during the last four ...

Studying real-world networks such as social networks or web networks is a challenge. These networks often combine a complex, highly connected structure together with a large size. We propose a new approach for large scale networks that is able to automatic ...

Benjamin Ricaud

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A Time-Vertex Signal Processing Framework

Transient networks of spatio-temporal connectivity map communication pathways in brain functional systems

Vertex-Frequency Analysis on Graphs

Fourier could be a data scientist: From graph Fourier transform to signal processing on graphs

An optimally concentrated Gabor transform for localized time-frequency components

Refined Support and Entropic Uncertainty Inequalities

On the optical properties of carbon nanotubes. Part I. A general formula for the dynamical optical conductivity

Principal Patterns on Graphs: Discovering Coherent Structures in Datasets

Anomaly detection in the dynamics of web and social networks

Tracking Time-Vertex Propagation using Dynamic Graph Wavelets

System, device, and method for contextual knowledge retrieval and display

Locating Temporal Functional Dynamics of Visual Short-Term Memory Binding using Graph Modular Dirichlet Energy

On the Sparsity of Wavelet Coefficients for Signals on Graphs

Learnable filter-banks for CNN-based audio applications

Naviguer dans les traces numériques sur Twitter. Retour sur la conception d’un dispositif de cartographie de données à destination de journalistes

A survey of uncertainty principles and some signal processing applications

What is Trending on Wikipedia? Capturing Trends and Language Biases Across Wikipedia Editions

Mapping resting-state dynamics on spatio-temporal graphs: a combined functional and diffusion MRI approach

Spikyball Sampling: Exploring Large Networks via an Inhomogeneous Filtered Diffusion