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A new spatial count data model with Bayesian additive regression trees for accident hot spot identification

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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

A new spatial count data model with Bayesian additive regression trees for accident hot spot identification

Graph Chatbot

Chattez avec Graph Search

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Boosting likelihood learning with event reweighting

Extensions of Peer Prediction Incentive Mechanisms

Residual-based attention in physics-informed neural networks

On the use of Cramér-Rao Lower Bound for least-variance circuit parameters identification of Li-ion cells

Training a Filter-Based Model of the Cochlea in the Context of Pre-Trained Acoustic Models

Partial discharge localization in power transformer tanks using machine learning methods

Generalized Bradley-Terry Models for Score Estimation from Paired Comparisons

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Boosting likelihood learning with event reweighting

Extensions of Peer Prediction Incentive Mechanisms

Residual-based attention in physics-informed neural networks

On the use of Cramér-Rao Lower Bound for least-variance circuit parameters identification of Li-ion cells

Training a Filter-Based Model of the Cochlea in the Context of Pre-Trained Acoustic Models

Partial discharge localization in power transformer tanks using machine learning methods

Generalized Bradley-Terry Models for Score Estimation from Paired Comparisons

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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