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Networks of Coupled VO2 Oscillators for Neuromorphic Computing

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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

Networks of Coupled VO2 Oscillators for Neuromorphic Computing

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

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

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Random matrix methods for high-dimensional machine learning models

Experimental observation of topological transition in linear and nonlinear parametric oscillators

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Generalization of Scaled Deep ResNets in the Mean-Field Regime

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

Aggregating Spatial and Photometric Context for Photometric Stereo

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

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

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Random matrix methods for high-dimensional machine learning models

Experimental observation of topological transition in linear and nonlinear parametric oscillators

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Generalization of Scaled Deep ResNets in the Mean-Field Regime

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

Aggregating Spatial and Photometric Context for Photometric Stereo

Deep Learning Theory Through the Lens of Diagonal Linear Networks