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The shine-through paradigm and the schizophrenia spectrum: a summary

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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

The shine-through paradigm and the schizophrenia spectrum: a summary

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Chattez avec Graph Search

InterpretCC: Intrinsic User-Centric Interpretability through Global Mixture of Experts

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

Generalization of Scaled Deep ResNets in the Mean-Field Regime

33.3 MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes

Ethological computational psychiatry: Challenges and opportunities

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Enabling Uncertainty Estimation in Iterative Neural Networks

Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object Exchange

Unveiling the complexity of learning and decision-making

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

InterpretCC: Intrinsic User-Centric Interpretability through Global Mixture of Experts

33.3 MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Enabling Uncertainty Estimation in Iterative Neural Networks

Unveiling the complexity of learning and decision-making

Ethological computational psychiatry: Challenges and opportunities

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object Exchange

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks