The Societal and Scientific Importance of Inclusivity, Diversity, and Equity in Machine Learning for Chemistry

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Deep neural networks form the backbone of artificial intelligence (AI) research, with potential to transform the human experience in areas ranging from autonomous driving to personal assistants, healthcare to education. However, their integration into the ...

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 ...

This study investigates Quantum Extreme Learning Machines (QELMs), which enhance classical Extreme Learning Machines (ELMs) by incorporating quantum features. ...

Recent advancements in deep learning have revolutionized 3D computer vision, enabling the extraction of intricate 3D information from 2D images and video sequences. This thesis explores the application of deep learning in three crucial challenges of 3D com ...

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

This thesis addresses key challenges in developing adaptive lower-limb exoskeletons to enhance balance, mobility, and user autonomy during daily living activities. It presents a comprehensive exploration of three critical aspects: push recovery during stan ...

Driven by the need for more efficient and seamless integration of physical models and data, physics -informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains ...

Thermal scene reconstruction holds great potential for various applications, such as building energy analysis and non-destructive infrastructure testing. However, existing methods rely on dense scene measurements and use RGB images for 3D reconstruction, i ...

Defending aligned Large Language Models (LLMs) against jailbreaking attacks is a challenging problem, with existing approaches requiring multiple requests or even queries to auxiliary LLMs, making them computationally heavy. Instead, we focus on detecting ...

Despite the widespread use of self-tracking technologies for promoting personal wellbeing, there is limited research on the monitoring of intimate data, particularly urine. To shed light on the design possibilities within this unexplored domain we designed ...

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

In this thesis we will present two results on global existence for nonlinear dispersive equations with data at or below the scaling regularity. In chapter 1 we take a probabilistic perspective to study the energy-critical nonlinear Schrödinger equation in ...

Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data st ...

The Societal and Scientific Importance of Inclusivity, Diversity, and Equity in Machine Learning for Chemistry

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A Human-Centric Approach to Explainable AI for Personalized Education

Incorporating Projective Geometry into Deep Learning

Harnessing Photon Indistinguishability in Quantum Extreme Learning Machines

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Partial Assistance with Lower-Limb Exoskeletons to Enhance Gait and Balance in Daily Living Activities

Residual-based attention in physics-informed neural networks

ThermoNeRF: A multimodal Neural Radiance Field for joint RGB-thermal novel view synthesis of building facades

Single-pass Detection of Jailbreaking Input in Large Language Models

Designing for Intimate Wellbeing: Aidee, a Qualitative Approach To Urine Home Monitoring

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

Probabilistic and Deterministic Wellposedness for Low Regularity Dispersive Equations

Orchestrating chromosome conformation capture analysis with Bioconductor