Sampling Geometry and Colour

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Publications associées (31)

Graph signal processing tailored for subgraph focus and community structure

Miljan Petrovic

Community structure in graph-modeled data appears in a range of disciplines that comprise network science. Its importance relies on the influence it bears on other properties of graphs such as resilience, or prediction of missing connections. Nevertheless, ...

EPFL2022

Reduced representations of complexes, signals, and multifiltrations

Celia Camille Hacker

The field of computational topology has developed many powerful tools to describe the shape of data, offering an alternative point of view from classical statistics. This results in a variety of complex structures that are not always directly amenable for ...

EPFL2022

Auditory externalization of a remote microphone signal

Vincent Pierre Olivier Grimaldi

A remote microphone (RM) system can be used in combination with wearable binaural communication devices, such as hearing aids (HAs), to improve speech intelligibility. Typically, a speaker is equipped with a body-worn microphone which enables to pick up th ...

EPFL2022

Engineering of Existing Structures: The Need and Place for Non-destructive Evaluation

Eugen Brühwiler, Numa Joy Bertola, Thomas Schumacher

Structural engineers today are still educated mainly to design new structures. This ignores the fact that structures already exist and need to be maintained. Students are thus often ill-equipped to deal with maintenance and preservation of existing structu ...

2022

Quantization for Distributed Processing and Learning of Structured Data

Isabela Cunha Maia Nobre

In the domains of machine learning, data science and signal processing, graph or network data, is becoming increasingly popular. It represents a large portion of the data in computer, transportation systems, energy networks, social, biological, and other s ...

EPFL2022

Timing is Everything

Karen Adam

In this thesis, timing is everything. In the first part, we mean this literally, as we tackle systems that encode information using timing alone. In the second part, we adopt the standard, metaphoric interpretation of this saying and show the importance of ...

EPFL2022

All-optical switching in epsilon-near-zero asymmetric directional coupler

Qian Li, Jiaye Wu

We propose an all-optical switch based on an asymmetric directional coupler structure with epsilon-near-zero (ENZ) layer. The nonlinear optical properties the of ENZ layer are analyzed by hot-electron dynamics process, and the all-optical operating perform ...

Nature Portfolio2022

Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function

Patrick Thiran, Saber Salehkaleybar, Negar Kiyavash

We study the performance of Stochastic Cubic Regularized Newton (SCRN) on a class of functions satisfying gradient dominance property with

1\le\alpha\le2

which holds in a wide range of applications in machine learning and signal processing. This conditio ...

NeurIPS2022

Step Change Detection for Improved ROCOF Evaluation of Power System Waveforms

Mario Paolone, Asja Derviskadic, Guglielmo Frigo, Alexandra Cameron Karpilow

In the analysis of power grid waveforms, the presence of amplitude or phase steps can disrupt the estimation of frequency and rate-of-change-of-frequency (ROCOF). Standard methods based on phasor-models fail in the extraction of signal parameters during th ...

IEEE2022

Parallel temporal signal processing enabled by polarization-multiplexed programmable THz metasurfaces

Romain Christophe Rémy Fleury, Ali Momeni

Under the trends of multifunctionality, tunability, and compactness in modern wave -based signal processors, in this paper, we propose a polarization-multiplexed graphene-based metasurface to realize distinct mathematical operators on the parallel time-dom ...

Optica Publishing Group2022

Generalised Implicit Neural Representations

Pierre Vandergheynst

We consider the problem of learning implicit neural representations (INRs) for signals on non-Euclidean domains. In the Euclidean case, INRs are trained on a discrete sampling of a signal over a regular lattice. Here, we assume that the continuous signal e ...

2022

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