Generative artificial intelligence (AI) and its applications offer significant benefits but raise potentially critical societal and ethical concerns. This thesis explores the field of synthetic content generation and detection, with a particular focus on synth…
The three-dimensional organization of the genome and the interactions between biomolecules are fundamental to understanding cellular function and disease. Recent advances in sequencing technologies and structural biology have generated unprecedented amounts of…
Chaotic dynamical systems are characterized by strong nonlinearity, aperiodic long-term behavior, and high sensitivity to initial conditions, which make their numerical simulation extremely demanding, especially in engineering-relevant applications such as tur…
Prostate cancer (PCa) remains among the most prevalent and deadly cancers among men worldwide, with rising incidence rates placing increasing pressure on healthcare systems. Magnetic Resonance Imaging (MRI), and more specifically, Diffusion-Weighted Imaging (D…
Modern wireless communication systems are increasingly required to operate under uncertain and heterogeneous conditions, spanning signal inference under unknown noise distributions, reliable transmission in the presence of adversarial interference, and adaptiv…
The past decade has seen significant advancements in generative models. As one of the most fundamental machine learning and computer vision tasks, generative models aim to produce realistic-looking synthetic samples by learning from real samples. However, trai…
The deployment of Deep Learning in safety-critical domains is hindered by pathological overconfidence and an inability to distinguish between aleatoric uncertainty (data ambiguity) and epistemic uncertainty (lack of knowledge). This thesis addresses these limi…
Recent advancements in Computer Vision (CV) and Machine Learning (ML) have fundamentally revolutionized the field of human behaviour understanding, enabling intelligent systems to move beyond simple motion detection to the interpretation of complex, semantic a…
Modern machine learning (ML) systems are increasingly required to operate in dynamic environments, where models must adapt to new information, remove obsolete or sensitive knowledge, and satisfy fairness and safety requirements. This thesis addresses these cha…
Over the past decade, deep learning has achieved significant breakthroughs in various domains, including computer vision and natural language processing, with applications spanning industries such as healthcare and manufacturing. However, the success of deep n…
Deep generative modeling is revolutionizing visual data synthesis, from creative industry applications to tools for scientific discovery in fields like medical imaging and remote sensing. In image synthesis, deep learning models like Variational Autoencoders (…
The topic of this thesis is the use of probabilistic methods in machine learning. These play a foundational role in motivating and defining machine learning algorithms, as well as in explaining why, and how well, the algorithms work. During the years in which…
أنا مساعد المستودع. اسألني عن الرسائل والأطاريح حسب الموضوع أو الجامعة أو الدولة أو السنة أو الدرجة، أو اطلب أعداداً وإحصاءات.
يجيب من قاعدة بيانات المستودع فقط، ولا يخترع سجلات أو أرقاماً. لا يُحفظ ما تكتبه على الخادم.
قد يخطئ المساعد أحياناً، فراجع المصادر المرفقة.
