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Faculty of Mathematics

 

I am a Research Fellow in Numerical Analysis.

My research interests lie at the intersection between numerical analysis and deep learning. I primarily focus on the mathematical foundations of deep learning to discover mathematical models (partial differential equations) from data, and the development of novel and theoretically justified numerical techniques.

I am a member of the Scientific Artificial Intelligence (SciAI) Center supported by the Office of Naval Research (ONR).

Publications

Bifurcation analysis of a two-dimensional magnetic Rayleigh-Bénard problem
F Laakmann, N Boullé
(2022)
Principled interpolation of Green's functions learned from data
H Praveen, N Boulle, C Earls
(2022)
Data-driven discovery of Green's functions
N Boullé
(2022)
Two-Component 3D Atomic Bose-Einstein Condensates Support Complex Stable Patterns
N Boullé, I Newell, PE Farrell, PG Kevrekidis
(2022)
Bifurcation analysis of two-dimensional Rayleigh-Benard convection using deflation
N Boullé, V Dallas, PE Farrell
– Phys Rev E
(2022)
105,
055106
Learning Green's functions associated with time-dependent partial differential equations
N Boullé, S Kim, T Shi, A Townsend
(2022)
Data-driven discovery of Green's functions with human-understandable deep learning
N Boullé, CJ Earls, A Townsend
– Scientific Reports
(2022)
12,
4824
Optimization of Hopf bifurcation points
N Boullé, PE Farrell, ME Rognes
(2022)
Learning Elliptic Partial Differential Equations with Randomized Linear Algebra
N Boullé, A Townsend
– Foundations of Computational Mathematics
(2022)
23,
709
Control of Bifurcation Structures using Shape Optimization
N Boullé, PE Farrell, A Paganini
– SIAM Journal on Scientific Computing
(2022)
44,
a57
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Research Group

Cambridge Image Analysis

Room

F2.05

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