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Self-Supervised Bayesian representation learning of acoustic emissions from laser powder bed Fusion process for in-situ monitoring

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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

Self-Supervised Bayesian representation learning of acoustic emissions from laser powder bed Fusion process for in-situ monitoring

Graph Chatbot

Chattez avec Graph Search

Unlabeled Principal Component Analysis and Matrix Completion

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

Incorporating Projective Geometry into Deep Learning

Understanding generalization and robustness in modern deep learning

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

Learning Informative Health Indicators Through Unsupervised Contrastive Learning

Reducing Annotation Efforts in Electricity Theft Detection Through Optimal Sample Selection

Residual-based attention in physics-informed neural networks

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

Understanding generalization and robustness in modern deep learning

Unlabeled Principal Component Analysis and Matrix Completion

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Incorporating Projective Geometry into Deep Learning

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

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

Residual-based attention in physics-informed neural networks

Reducing Annotation Efforts in Electricity Theft Detection Through Optimal Sample Selection

Learning Informative Health Indicators Through Unsupervised Contrastive Learning