Physics-based neural network for non-invasive control of coherent light in scattering media

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This thesis focuses on understanding and improving the reasoning capabilities of neural networks. It develops theoretical results and empirical analyses to uncover reasoning potential and limitations, leveraging these insights to guide the design of improv ...

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A search is presented for the pair production of new heavy resonances, each decaying into a top quark (t) or antiquark and a gluon (g). The analysis uses data recorded with the CMS detector from proton-proton collisions at a center-of-mass energy of 13 TeV ...

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Ultrafast ultrasound imaging achieves high frame rates but results in lower image quality compared to focused acquisitions. Convolutional neural networks (CNNs) have emerged as effective tools for reducing diffraction artifacts and enhancing the quality of ...

Physics-based neural network for non-invasive control of coherent light in scattering media

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Learning to Reason with Neural Networks: Principles and Methods

A comparative analysis of gene expression profiling by statistical and machine learning approaches

Spectroscopy of two-dimensional interacting lattice electrons using symmetry-aware neural backflow transformations

Search for Pair Production of Heavy Particles Decaying to a Top Quark and a Gluon in the Lepton Plus Jets Final State in Proton-proton Collisions at √s=13 Tev

Modelleyen: Continual Learning and Planning via Structured Modelling of Environment Dynamics

A Latent Implicit 3D Shape Model for Multiple Levels of Detail

Explainable modeling for wind power forecasting: A Glass-Box model with high accuracy

On the Perspectives of Image-to-Lidar Constraints in Dynamic Network Optimisation

Computational design of complex protein folds and soluble analogs of membrane proteins

Exploiting Representation Similarities in Self-Supervised Learning for Vision Tasks

Factor-graph Optimisation with Vehicle Dynamic Models for Mapping & Sensing Applications

High-performance deep spiking neural networks with 0.3 spikes per neuron

Sparse autoregressive neural networks for classical spin systems

Using Physical Dynamics: Accurate and Real-Time Object Detection for High-Resolution Video Streaming on Internet of Things Devices

Accelerating Dynamic Aperture Evaluation Using Deep Neural Networks

Learning-based Hierarchical Control: Emulating the Central Nervous System for Bio-Inspired Legged Robot Locomotion

Asymptotics of feature learning in two-layer networks after one gradient-step

Investigating the Effect of Misalignment on Membership Privacy in the White-box Setting

Using Motion Cues to Supervise Single-Frame Body Pose and Shape Estimation in Low Data Regimes

Enhancement of Ultrafast Ultrasound Images: A Performance Comparison Between CNN Trained with RF or IQ Images