Publications related to Unraveling brain interactions in vision: the example of crowding

Validation and Application of Hysteresis Loss Model for HTS Stacks and Conductors for Fusion Applications

Numerous conductor designs for pulsed magnets based on High Temperature Superconductors (HTS), featuring stacks of tapes are currently being proposed. A major contribution to the AC losses is expected to be given by hysteresis losses. Several numerical mod ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Dataset for '3D printing of customizable transient bioelectronics and sensors'

Danick Briand, Nicolas Francis Fumeaux

This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “3D printing of customizable transient bioelectronics and sensors”. This work aims to study and demonstrate ...

Zenodo2024

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

Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model

Wenlong Liao, Yi Zhang, Zhe Yang

Recently, remarkable progress has been made in the application of machine learning (ML) techniques (e.g., neural networks) to transformer fault diagnosis. However, the diagnostic processes employed by these techniques often suffer from a lack of interpreta ...

Piscataway2024

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

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

Data-driven statistical optimization of a groundwater monitoring network

Andrea Rinaldo, Gianluca Botter

We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurf ...

Elsevier2024

Sparse autoregressive neural networks for classical spin systems

Giuseppe Carleo, Dian Wu, Indaco Biazzo

Efficient sampling and approximation of Boltzmann distributions involving large sets of binary variables, or spins, are pivotal in diverse scientific fields even beyond physics. Recent advances in generative neural networks have significantly impacted this ...

Iop Publishing Ltd2024

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Ian Smith, Katrin Beyer, Bryan German Pantoja Rosero, Mathias Christian Haindl Carvallo

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

Springer2024

Training a Filter-Based Model of the Cochlea in the Context of Pre-Trained Acoustic Models

Philip Neil Garner

Auditory research aims in general to lead to understanding of physiological processes. By contrast, the state of the art in automatic speech processing (notably recognition) is dominated by large pre-trained models that are meant to be used as black-boxes. ...

2024

Unraveling brain interactions in vision: the example of crowding

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Validation and Application of Hysteresis Loss Model for HTS Stacks and Conductors for Fusion Applications

Dataset for '3D printing of customizable transient bioelectronics and sensors'

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Data-driven statistical optimization of a groundwater monitoring network

Sparse autoregressive neural networks for classical spin systems

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Training a Filter-Based Model of the Cochlea in the Context of Pre-Trained Acoustic Models

Dataset for '3D printing of customizable transient bioelectronics and sensors'

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Validation and Application of Hysteresis Loss Model for HTS Stacks and Conductors for Fusion Applications

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Sparse autoregressive neural networks for classical spin systems

Data-driven statistical optimization of a groundwater monitoring network

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Training a Filter-Based Model of the Cochlea in the Context of Pre-Trained Acoustic Models

Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model