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Remote sensing visual question answering with a self-attention multi-modal encoder

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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

Remote sensing visual question answering with a self-attention multi-modal encoder

Graph Chatbot

Chattez avec Graph Search

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

Driving and suppressing the human language network using large language models

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

Sparse autoregressive neural networks for classical spin systems

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

Random matrix methods for high-dimensional machine learning models

Topics in statistical physics of high-dimensional machine learning

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

Aggregating Spatial and Photometric Context for Photometric Stereo

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

Driving and suppressing the human language network using large language models

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

Sparse autoregressive neural networks for classical spin systems

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

Random matrix methods for high-dimensional machine learning models

Topics in statistical physics of high-dimensional machine learning

Aggregating Spatial and Photometric Context for Photometric Stereo

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

Deep Learning Theory Through the Lens of Diagonal Linear Networks