Scholar
Richard Bergna
Google Scholar ID: QEjxEjcAAAAJ
University of Cambridge
Citations & Impact
Citations
12
H-index
2
i10-index
0
Publications
6
Co-authors
5
list available
Publications
Resume (English only)
Academic Achievements
- Published a preprint titled 'Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations' which explores incorporating stochastic processes into graph neural networks for uncertainty handling; also an example conference paper on large language models.
Research Experience
- As a PhD student at the Cambridge Computational and Biological Learning Group (CBL), he has been involved in several research projects, mainly focusing on uncertainty quantification and related areas in machine learning.
Education
- PhD in Advanced Machine Learning, University of Cambridge, supervised by Prof. Jose Miguel Hernandez-Lobato and Prof. Pietro Liò; MPhil in Machine Learning and Machine Intelligence, University of Cambridge; BEng in Engineering Mathematics, University of Bristol, graduated with first-class honors.
Background
- Research interests include uncertainty quantification in ML, probabilistic deep learning, Bayesian methods, Gaussian processes, reinforcement learning, and graph neural networks. He is a PhD student at the Cambridge Computational and Biological Learning Group (CBL), focusing on uncertainty quantification with applications in decision-making under uncertainty, Gaussian processes, graph neural networks, and reinforcement learning.
Miscellany
- Personal interests not specifically mentioned
