Profile
Dr Andrew Corbett
Research Fellow
Telephone: 01392 723664
Extension: (Streatham) 3664
Research interests
- Machine learning, computer vision and object recognition.
- Deep neural networks, dynamical systems and optimal control.
- Explainable AI and understanding deep learning thought processes.
- Fourier analysis, number theory and representation theory.
- Exeter's Institute of Data Science and Artificial Intelligence.
- Machine Learning Lead at digiLab.
Pubications and preprints
Open access to journal articles may be found under the publications tab. More recent articles ahead of print are found below:
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twinCity: Urban Solar Potential on the City Scale, with B. Fourcin, M. Lykkegaard, T. Dodwell; To Appear (2024)
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VespAI: A Deep Learning-Based System for the Detection of Invasive Hornets, with T. O'Shea-Wheller, P. Kennedy, J. Osborne, M. Recker; To Appear (2024)
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Simulating spectral images of natural waters and submerged objects from a bird's-eye view, with J. Christmas, C. Lawrence, J Feenan; Math. Compt. Simul. (2024)
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Imbedding Deep Neural Networks, with D. Kangin; spotlighted at ICLR (2022)
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Voronoï summation for half-integral weight automorphic forms, with E. Assing; Int. Math. Res. Not. (2021)
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A symplectic restriction problem, with V. Blomer; Math. Ann. (2021)
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Voronoï summation via switching cusps, with E. Assing; Monatsh. Math. (2021)
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Voronoï summation for GL(n): collusion between level and modulus; Amer. J. Math. (2021)
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An explicit conductor formula for GL(n) x GL(1); Rocky Mountain J. Math. (2019)
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On the order of vanishing of newforms at cusps, with A. Saha; Math. Res. Lett. (2018)
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A proof of the refined Gan--Gross--Prasad conjecture for non-endoscopic Yoshida lifts; Forum Math. (2017)