Publications (4)
Symmetry Guarantees Statistic Recovery in Variational Inference
Daniel Marks, Dario Paccagnan, Mark van der Wilk
Variational inference (VI) is a central tool in modern machine learning, used to approximate an intractable target density by optimising over a tractable family of distributions. A…
Pick-to-Learn for Systems and Control: Data-driven Synthesis with State-of-the-art Safety Guarantees
Dario Paccagnan, Daniel Marks, Marco C. Campi +1
Data-driven methods have become paramount in modern systems and control problems characterized by growing levels of complexity. In safety-critical environments, deploying these met…
Interpretable histopathology-based prediction of disease relevant features in Inflammatory Bowel Disease biopsies using weakly-supervised deep learning
Ricardo Mokhtari, Azam Hamidinekoo, Daniel Sutton +12
Crohn's Disease (CD) and Ulcerative Colitis (UC) are the two main Inflammatory Bowel Disease (IBD) types. We developed deep learning models to identify histological disease feature…
Computational Microwave Imaging Using 3D Printed Conductive Polymer Frequency-Diverse Metasurface Antennas
Okan Yurduseven, Patrick Flowers, Shengrong Ye +5
A frequency-diverse computational imaging system synthesized using three-dimensional (3D) printed frequency-diverse metasurface antennas is demonstrated. The 3D fabrication of the…