Exploring quantum perceptron and quantum neural network structures with a teacher-student scheme

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In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

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Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

Exploring quantum perceptron and quantum neural network structures with a teacher-student scheme

Chat with Graph Search

From Pose to Behavior: Advancing Multi-Individual Pose Estimation and Hierarchical Action Segmentation with Transformers

Fully data-driven and modular building thermal control with physically consistent modeling

Machine learning enhanced tomographic reconstruction for multispectral imaging on TCV

Rapid prediction of phonon density of states by crystal attention graph neural network and high-throughput screening of candidate substrates for wide bandgap electronic cooling

EntitySAM: Segment Everything in Video

Explainable AI guided unsupervised fault diagnostics for high-voltage circuit breakers

Predicting High-magnification Events in Microlensed Quasars in the Era of LSST Using Recurrent Neural Networks

ChemLit-QA: a human evaluated dataset for chemistry RAG tasks

NNG-Mix: Improving Semi-Supervised Anomaly Detection with Pseudo-Anomaly Generation

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Random matrix methods for high-dimensional machine learning models

Topics in statistical physics of high-dimensional machine learning

Empirical Sample Complexity of Neural Network Mixed State Reconstruction

On the number of regions of piecewise linear neural networks

Quantum Protocols for ML, Physics, and Finance

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

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Structure-based drug design with equivariant diffusion models

Ultra-high quantum coherent and scalable superconducting circuit optomechanics, from topological lattices to quantum storage

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation