Publications associées à A Learning-Based Framework for Quantized Compressed Sensing

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Random sampling of bandlimited signals on graphs

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

We study the problem of sampling

k

-bandlimited signals on graphs. We propose two sampling strategies that consist in selecting a small subset of nodes at random. The first strategy is non-adaptive, \ie, independent of the graph structure, and its perform ...

2015

A Learning-Based Framework for Quantized Compressed Sensing

Graph Chatbot

Chattez avec Graph Search

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

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Random sampling of bandlimited signals on graphs

Too much success for recent groundbreaking epigenetic experiments

Sampling based on timing: Time encoding machines on shift-invariant subspaces

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Shapes from Pixels

Random sampling of bandlimited signals on graphs

Geology Basics for Engineers

Sampling based on timing: Time encoding machines on shift-invariant subspaces

Just Sort It! A Simple and Effective Approach to Active Preference Learning

Safe Adaptive Importance Sampling

An Algorithm for Formation-Based Chemical Plume Tracing Using Robotic Marine Vehicles

Compressive Spectral Clustering

Too much success for recent groundbreaking epigenetic experiments