Most of the success of deep learning in computer vision depends on supervised learning (SL) and large-scale, manually annotated datasets. Creating such datasets is a major bottleneck due to the substantial cost and labor required, particularly for pixel-level…
Transformer language models (LMs), the cornerstone of the popular large language models (LLMs), have revolutionised the fields of artificial intelligence (AI) and natural language processing (NLP). However, we still understand relatively little about their com…
Transformers and Large Language Models have achieved incredible performance in deep learning, especially in natural language processing, and a precise understanding of the internal mechanisms driving their success is essential. We first provide an empirical an…
Stock price prediction is a common and complex problem due to the high volatility of financial markets. This master’s thesis presents a new approach to stock price forecasting by reformulating the problem as a multiclass classification task. The main objective…
The increasing reliance on Industrial Control Systems (ICS) and Supervisory Control and Data Acquisition (SCADA) systems has raised critical concerns regarding their vulnerability to cyberattacks. While machine learning (ML) methods have emerged as effective t…
Background The rapid growth of medical literature necessitates effective, transparent automation tools for classification. Generative large language models (LLMs), including the Generative Pre-trained Transformer (GPT), have the potential to provide transparen…
Understanding the threat landscape of cyber-physical systems is crucial for developing effective defenses against emerging, highly sophisticated cyber threats. This understanding demands two essential components: the ability to predict the sophisticated behavi…
In the field of Electronic Design Automation (EDA), dividing a complex circuit into smaller subcircuits is a critical step. This process, known as circuit partitioning, minimizes the connections needed between these subcircuits while dividing the overall desig…
Circuit clustering and circuit partitioning are essential tasks in the Very Large Scale Integration (VLSI) design flow and are usually solved using algorithmic techniques. Graph Neural Networks (GNNs), a branch of artificial neural networks, leverage the predi…
Slang is a common type of language that makes creative and highly flexible use of words. A basic problem that language users tackle is how to develop and interpret novel slang terms for communication in a community. This problem is relevant for natural languag…
In the development of smart cities, the integration of Internet of Things (IoT) and Artificial Intelligence (AI) technologies promises to address urban challenges yet raises significant security and ethical concerns. This study emphasizes the need for robust g…
The discovery of X-rays marked a significant milestone in the field of medicine. One of the most common types of X-rays, the chest X-ray (CXR), allows doctors to examine an individual’s internal structure without surgery. Over the years, deep learning methods…
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