Optimal Sampling Rates in Infinite-Dimensional Compressed Sensing

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

In inverse problems, the task is to reconstruct an unknown signal from its possibly noise-corrupted measurements. Penalized-likelihood-based estimation and Bayesian estimation are two powerful statistical paradigms for the resolution of such problems. They ...

Predicting the evolution of systems with spatio-temporal dynamics in response to external stimuli is essential for scientific progress. Traditional equations-based approaches leverage first principles through the numerical approximation of differential equ ...

The reported rate of the occurrence of unilateral spatial neglect (USN) is highly variable likely due to the lack of validity and low sensitivity of classical tools used to assess it. Virtual reality (VR) assessments try to overcome these limitations by pr ...

Speech recognition-based applications upon the advancements in artificial intelligence play an essential role to transform most aspects of modern life. However, speech recognition in real-life conditions (e.g., in the presence of overlapping speech, varyin ...

Years of a fierce competition have naturally selected the fittest deep learning algorithms. Yet, although these models work well in practice, we still lack a proper characterization of why they do so. This poses serious questions about the robustness, trus ...

The usual explanation of the efficacy of wavelet-based methods hinges on the sparsity of many real-world objects in the wavelet domain. Yet, standard wavelet-shrinkage techniques for sparse reconstruction are not competitive in practice, one reason being t ...

The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular via a few distinct techniques: the use of radar polarimetry, of multi-frequency radar measurements, and of the radar Doppler spectr ...

In the current era of big data, aggregation queries on high-dimensional datasets are frequently utilized to uncover hidden patterns, trends, and correlations critical for effective business decision-making. Data cubes facilitate such queries by employing p ...

This thesis is a study of the global well-posedness of the Cauchy problems for half-wave maps from the Minkowski space of dimension n+1 to the 2-dimensional sphere and the hyperbolic plane. The work is mainly based on the results from Krieger-Sire 17' in ...

Tensor trains are a versatile tool to compress and work with high-dimensional data and functions. In this work we introduce the streaming tensor train approximation (STTA), a new class of algorithms for approximating a given tensor ' in the tensor train fo ...

We present Epidemic Learning ( EL ), a simple yet powerful decentralized learning (DL) algorithm that leverages changing communication topologies to achieve faster model convergence compared to conventional DL approaches. At each round of EL, each node sen ...

Exploiting the recent advancements in artificial intelligence, showcased by ChatGPT and DALL-E, in real-world applications necessitates vast, domain-specific, and publicly accessible datasets. Unfortunately, the scarcity of such datasets poses a significan ...

A sample of 1.3 x 10^(5) K^(+) → π^(0)e^(+)νγ candidates with less than 1% background was collected by the NA62 experiment at the CERN SPS in 2017-2018. Branching fraction measurements are obtained at percent relative precision in three restricted kinemati ...

DNA methylation (DNAm) is one of the most frequently studied epigenetic mechanisms facilitating the interplay of genomic and environmental factors, which can contribute to externalizing behaviours and related psychiatric disorders. Previous epigenome-wide ...

The goal of this thesis is to study continuous-domain inverse problems for the reconstruction of sparse signals and to develop efficient algorithms to solve such problems computationally. The task is to recover a signal of interest as a continuous function ...

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 ...

In motor-related brain regions, movement intention has been successfully decoded from invivo spike train by isolating a lower-dimension manifold that the high-dimensional spiking activity is constrained to. The mechanism enforcing this constraint remains u ...

A microcasting process is used to produce high aspect ratio ( > 30) monocrystalline pure aluminium wires with a diameter between 14 and 115 mu m. The role of thermal activation in the plastic deformation of these microwires is measured by means of (single) ...

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 ...

We present a general framework for portfolio risk management in discrete time, based on a replicating martingale. This martingale is learned from a finite sample in a supervised setting. Our method learns the features necessary for an effective low-dimensi ...

Optimal Sampling Rates in Infinite-Dimensional Compressed Sensing

Chat with Graph Search

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

An immersive virtual reality tool for assessing left and right unilateral spatial neglect

Sparse Autoencoders for Speech Modeling and Recognition

The inductive bias of deep learning: Connecting weights and functions

The Sparsity of Cycle Spinning for Wavelet-Based Solutions of Linear Inverse Problems

Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

Well-posedness Issues For the Half-Wave Maps Equation With Hyperbolic And Spherical Targets

STREAMING TENSOR TRAIN APPROXIMATION

Epidemic Learning: Boosting Decentralized Learning with Randomized Communication

Dated: Guidelines for Creating Synthetic Datasets for Engineering Design Applications

A study of the K^(+) → π^(0)e^(+)νγ decay

Epigenome-wide DNA methylation in externalizing behaviours: A review and combined analysis

Variational Methods For Continuous-Domain Inverse Problems: the Quest for the Sparsest Solution

Timing is Everything

Topology of synaptic connectivity constrains neuronal stimulus representation, predicting two complementary coding strategies

The thermally activated deformation behaviour of single-crystalline microcast aluminium wires

Reduced representations of complexes, signals, and multifiltrations

A machine learning approach to portfolio pricing and risk management for high-dimensional problems