Representation learning algorithms for inferring machine independent latent features in pedestals in JET and AUG

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SAMPa: Sharpness-aware Minimization Parallelized

Volkan Cevher, Thomas Michaelsen Pethick, Wanyun Xie

Sharpness-aware minimization (SAM) has been shown to improve the generalization of neural networks. However, each SAM update requires sequentially computing two gradients, effectively doubling the per-iteration cost compared to base optimizers like SGD. We ...

2024

ProGAP: Progressive Graph Neural Networks with Differential Privacy Guarantees

Daniel Gatica-Perez, Sina Sajadmanesh

Graph Neural Networks (GNNs) have become a popular tool for learning on graphs, but their widespread use raises privacy concerns as graph data can contain personal or sensitive information. Differentially private GNN models have been recently proposed to p ...

Assoc Computing Machinery2024

Learning Weakly Convex Regularizers for Convergent Image-Reconstruction Algorithms

Michaël Unser, Alexis Marie Frederic Goujon, Sebastian Jonas Neumayer

We propose to learn non-convex regularizers with a prescribed upper bound on their weak-convexity modulus. Such regularizers give rise to variational denoisers that minimize a convex energy. They rely on few parameters (less than 15,000) and offer a signal ...

2024

Experimental characterization of the TCV dual-frequency gyrotron and validation of numerical codes including the effect of After Cavity Interaction

Timothy Goodman, Stefano Alberti, Jean-Philippe Hogge, Damien Fasel, Jérémy Genoud, Ugo Siravo, Jérémie Dubray, Matthieu Toussaint, Falk Hans Braunmüller, François Jean Gaston Legrand

A dual-frequency gyrotron has been developed within the context of the recent Tokamak à Configuration Variable (TCV) upgrade. The gyrotron is designed to generate a 1 MW, 2 seconds RF wave at 84 or 126 GHz. Before integrating the gyrotrons in the TCV tokam ...

2024

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

Marta Knezevic, Tanja Christina Käser Jacober, Jibril Albachir Frej, Tatjana Nazaretsky

The increasing availability of Massive Open Online Courses (MOOCs) has created a necessity for personalized course recommendation systems. These systems often combine neural networks with Knowledge Graphs (KGs) to achieve richer representations of learners ...

Assoc Computing Machinery2024