Model-based reinforcement learning and navigation in animals and machines

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Image steganalysis, detecting hidden data in digital images, is essential for enhancing digital security. Traditional steganalysis methods typically rely on large, pre-labeled image datasets, which are difficult and costly to compile. To address this, this ...

In the past few years, Machine Learning (ML) techniques have ushered in a paradigm shift, allowing the harnessing of ever more abundant sources of data to automate complex tasks. The technical workhorse behind these important breakthroughs arguably lies in ...

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Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, ...

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The first two chapters develop ML-based models that generate conditional SDF estimates efficiently using conditioning information sets, resulting in minimal pricing errors and superior Sharpe ratios compared to traditional conditional asset pricing models. ...

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

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In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

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The digitization of 3D deformable objects remains a significant challenge in computer graphics and vision, particularly in the accurate modeling of garments. Garments exhibit complex shape variability, non-rigid deformations, and frequent self-occlusion, m ...

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

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To retrieve Surface Solar Radiation (SSR) from satellite images, a baseline reflectance of the observed ground in clear-sky conditions, also called background reflectance, is necessary to distinguish atmospheric absorption and scattering effects from surfa ...

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Model-based reinforcement learning and navigation in animals and machines

Chat with Graph Search

Image steganalysis using active learning and hyperparameter optimization

Topics in statistical physics of high-dimensional machine learning

Application of Deep Learning and Geospatial Analysis in Soil Loss Risk in the Moulouya Watershed, Morocco

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

Machine learning-enabled estimation of cardiac output from peripheral waveforms is independent of blood pressure measurement location in an in silico population

Machine Learning Applications to Conditional Asset Pricing: Attention, CNNs, and Neural Tangent Kernels

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

Harnessing deep learning to detect bronchiolitis obliterans syndrome from chest CT

Incorporating Projective Geometry into Deep Learning

t-PiNet: A thermodynamics-informed hierarchical learning for discovering constitutive relations of geomaterials

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

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

Neural Garment Modeling

Deep Learning Theory Through the Lens of Diagonal Linear Networks

A Study on Quantum Graph Neural Networks Applied to Molecular Physics

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Combining physics-based and data-driven models: advancing the frontiers of research with scientific machine learning

Safe Deep Neural Networks

Retrieval of Surface Solar Radiation through Implicit Albedo Recovery from Temporal Context

Random matrix methods for high-dimensional machine learning models