Deep Learning
About
Deep learning studies a class of algorithms, based on artificial neural networks, that learn representations from data and compute with those representations. These algorithms are simple and perform remarkably well in tasks across computer vision, speech recognition, natural language processing and many other areas, including the natural sciences. The search for a theory of deep learning raises many new and difficult problems for mathematicians.
Group website
Academic Staff
Dr Jesse GELL-REDMAN (Lecturer)
Research interests: Microlocal analysis, Partial Differential Equations, Differential geometry
Dr Mingming GONG (Lecturer)
Research interests: Machine Learning, Causal Reasoning, Computer Vision
Dr Daniel MURFET (Lecturer)
Research interests: Mathematical logic, Algebraic geometry, Topological field theories
Dr Thomas QUELLA (Senior Lecturer)
Research interests: Representation Theory and Applications, Conformal field theory, quantum integrable models, Topological states of matter, tensor network states, Lie (super) algebras, diagram algebras, quantum groups, Quantum many-body physics
Dr Susan WEI (Lecturer)
Research interests: Statistical inference for big data, Machine Learning, Data Science
Postgraduate Students
COLMAN Owen
LI Hui
LIU Jayson
TRINH Allan
ZHANG Jiyuan
Honours & Masters (RT) Students
ANAGNOSTOU Lukas
PRYOR Robert
QUAN Yiran
SAVVINOS Alexius
TROIANI William
YANG Yijing
ZHU Yaoyao