Learning Parametric Dictionaries for Signals on Graphs

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Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...

Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...

In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

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\gamma

and momentum parameter

\beta

that allows u ...

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This dataset contains a collection of ultrafast ultrasound acquisitions from nine volunteers and the CIRS 054G phantom. For a comprehensive understanding of the dataset, please refer to the paper: Viñals, R.; Thiran, J.-P. A KL Divergence-Based Loss for In ...

The present work proposes a framework for nonlinear model order reduction based on a Graph Convolutional Autoencoder (GCA-ROM). In the reduced order modeling (ROM) context, one is interested in obtaining real -time and many-query evaluations of parametric ...

Digital twins are virtual models of physical objects or systems that enable real-time monitoring and analysis. In the ﬁeld of stone masonry buildings, digital twins can be used to assess damage, predict maintenance needs, and opti- mize building performanc ...

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 ...

The way biological brains carry out advanced yet extremely energy efficient signal processing remains both fascinating and unintelligible. It is known however that at least some areas of the brain perform fast and low-cost processing relying only on a smal ...

Learning Parametric Dictionaries for Signals on Graphs

Chat with Graph Search

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Incorporating Projective Geometry into Deep Learning

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Robust NAS under adversarial training: benchmark, theory, and beyond

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Machine Learning Security Against Data Poisoning: Are We There Yet?

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (3/6)

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

Digital Twins of Stone Masonry Buildings for Damage Assessment

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

Supervised learning and inference of spiking neural networks with temporal coding