In-Sensor Passive Speech Classification with Phononic Metamaterials

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

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

Optothermal shaping of lamb waves with square and spiral phase fronts

Romain Christophe Rémy Fleury, Aleksi Antoine Bossart, Janez Rus

We introduce a Lamb-wave medium with tunable propagation velocities, which are controlled by a two-dimensional heating pattern produced by a laser beam. We utilized it to demonstrate that waves in an appropriately designed medium can propagate in the form ...

2024

Enabling Wide Bandwidth in Substrate-Integrated Waveguide Slot Antennas by Using Low-Index Metamaterials

Romain Christophe Rémy Fleury, Amir Jafargholi, Jalaledin Tayebpour

This paper presents a solution to overcome the inherently limited bandwidth of substrate-integrated waveguide (SIW) slot antennas. It is analytically shown that by decreasing the permittivity of a dielectric loaded slot antenna, the resulting bandwidth inc ...

American Physical Society (APS)2024

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

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

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Seyed Mohammad Mahdi Johari

Recent advancements in deep learning have revolutionized 3D computer vision, enabling the extraction of intricate 3D information from 2D images and video sequences. This thesis explores the application of deep learning in three crucial challenges of 3D com ...

EPFL2024

Robust machine learning for neuroscientific inference

Steffen Schneider

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

EPFL2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Solar-assisted clean steam generator, a cleaner production approach for sustainable healthcare facilities

Fernando Porté Agel, Mohammad Jamshidmofid, Ahmad Arabkoohsar

Healthcare sector buildings, particularly hospitals, significantly contribute to global energy consumption and greenhouse gas emissions. Hospitals require a substantial amount of steam, including the essential hygienic or " clean steam, " that is currently ...

Elsevier Sci Ltd2024

Random matrix methods for high-dimensional machine learning models

Antoine Philippe Michel Bodin

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

EPFL2024

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