Impact of Memory Voltage Scaling on Accuracy and Resilience of Deep Learning Based Edge Devices

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Electrical and Optical Manifestations of Flat Band Physics in Van der Waals Materials

The scientific progress is significantly transforming contemporary society with the introduction and widespread application of technologies like artificial intelligence and quantum computing. Despite their profound impact, these technologies necessitate en ...

EPFL2024

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Mattia Atzeni

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

Static and Dynamic Voltage Balancing for an IGCT-Based Resonant DC Transformer

Drazen Dujic, Nikolina Djekanovic, Renan Pillon Barcelos

This paper focuses on the operational characteristics of a medium voltage resonant DC transformer based on a split capacitor IGCT 3L-NPC leg. The study delves into both the dynamic and static balancing aspects of the 3L-NPC when operating in a two-level, 5 ...

2024

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Arnout Jan J Devos

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

EPFL2024

Phase Shift Angle Segmentation Modulation for Soft-Switching Medium-Voltage DAB Converter With Series-Connected SiC MOSFETs

Heng Fang, Rui Lu, Chengmin Li

The medium-voltage (MV) dual active bridge (DAB) converter with series-connected SiC (S-SiC) MOSFETs is a promising solution for high-power-density isolated dc/dc converter. To improve the voltage sharing and reliability of S-SiC, relatively large snubber ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Claudio Bruschini, Edoardo Charbon, Andrei Ardelean, Paul Mos, Yang Lin

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, ...

Nature Portfolio2024

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Michele Bianco, Jean-Paul Richard Kneib, Emma Elizabeth Tolley, Tianyue Chen

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Oxford Univ Press2024

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Scott William Pesme

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

2

-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

EPFL2024

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Romain Christophe Rémy Fleury, Janez Rus

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

2024

Error estimates for SUPG-stabilised Dynamical Low Rank Approximations

Fabio Nobile, Thomas Simon Spencer Trigo Trindade

We perform an error analysis of a fully discretised Streamline Upwind Petrov Galerkin Dynamical Low Rank (SUPG-DLR) method for random time-dependent advection-dominated problems. The time integration scheme has a splitting-like nature, allowing for potenti ...

Springer Nature Switzerland2025

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Alexander Carl Unnervik

The field of biometrics, and especially face recognition, has seen a wide-spread adoption the last few years, from access control on personal devices such as phones and laptops, to automated border controls such as in airports. The stakes are increasingly ...

EPFL2024

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