Methods and systems for noise resilient, pin-efficient and low power communications with sparse signaling codes

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Methods and systems for noise resilient, pin-efficient and low power communications with sparse signaling codes

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

A Two-Wired High Input Impedance and High CMRR Active Electrode Insensitive to Component Mismatch

Federated Linear Bandit Learning via Over-the-air Computation

Sparse Autoencoders for Speech Modeling and Recognition

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

Towards learning-based denoising of light fields

Image scanning microscopy with a doughnut beam: signal strength and integrated intensity

Quantification of the Phenomena Affecting Reflective Arterial Photoplethysmography

(S)GD over Diagonal Linear Networks: Implicit Regularisation, Large Stepsizes and Edge of Stability

Finding information-rich electrocardiographic biomarkers to characterize atrial fibrillation

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

The SparSpec algorithm and the application to the detection of spatial periodicities in tokamaks: from a 1D to a 2D analysis

From Undercomplete to Sparse Overcomplete Autoencoders to Improve LF-MMI Speech Recognition

Spike-Based Sensing and Communication for Highly Energy-Efficient Sensor Edge Nodes

Generalised Implicit Neural Representations

Graph signal processing tailored for subgraph focus and community structure

A Delta Sigma-Modulated Sample and Average Common-Mode Feedback Technique for Capacitively Coupled Amplifiers in a 192-nW Acoustic Analog Front-End

A framework for occupancy detection and tracking using floor-vibration signals

Quantization for Distributed Processing and Learning of Structured Data

Systems and methods for energy-efficient measurement of neurophysiological oscillations