Andrew Duncan
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Variance reduction using nonreversible Langevin samplers
AB Duncan, T Lelievre, GA Pavliotis
Journal of statistical physics 163 (3), 457-491, 2016
Measuring sample quality with diffusions
J Gorham, AB Duncan, SJ Vollmer, L Mackey
The Annals of Applied Probability 29 (5), 2884-2928, 2019
Noise-induced multistability in chemical systems: Discrete versus continuum modeling
A Duncan, S Liao, T Vejchodský, R Erban, R Grima
Physical Review E 91 (4), 042111, 2015
Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains
J Bierkens, A Bouchard-Côté, A Doucet, AB Duncan, P Fearnhead, ...
Statistics & Probability Letters 136, 148-154, 2018
The true cost of stochastic gradient Langevin dynamics
T Nagapetyan, AB Duncan, L Hasenclever, SJ Vollmer, L Szpruch, ...
arXiv preprint arXiv:1706.02692, 2017
Hybrid framework for the simulation of stochastic chemical kinetics
A Duncan, R Erban, K Zygalakis
Journal of Computational Physics 326, 398-419, 2016
Using perturbed underdamped Langevin dynamics to efficiently sample from probability distributions
AB Duncan, N Nüsken, GA Pavliotis
Journal of Statistical Physics 169 (6), 1098-1131, 2017
Limit theorems for the Zig-Zag process
J Bierkens, A Duncan
arXiv Preprint arXiv:1607.08845, 2016
Nonreversible Langevin samplers: Splitting schemes, analysis and implementation
AB Duncan, GA Pavliotis, KC Zygalakis
arXiv preprint arXiv:1701.04247, 2017
Minimum stein discrepancy estimators
A Barp, FX Briol, A Duncan, M Girolami, L Mackey
Advances in Neural Information Processing Systems, 12964-12976, 2019
Note on A. Barbour's paper on Stein's method for diffusion approximations
MJ Kasprzak, AB Duncan, SJ Vollmer
Noise-induced transitions in rugged energy landscapes
AB Duncan, S Kalliadasis, GA Pavliotis, M Pradas
Physical Review E 94 (3), 032107, 2016
Statistical inference for generative models with maximum mean discrepancy
FX Briol, A Barp, AB Duncan, M Girolami
arXiv preprint arXiv:1906.05944, 2019
On the geometry of Stein variational gradient descent
A Duncan, N Nuesken, L Szpruch
arXiv preprint arXiv:1912.00894, 2019
Spatial Flow-Field Approximation Using Few Thermodynamic Measurements—Part II: Uncertainty Assessments
P Seshadri, A Duncan, D Simpson, G Thorne, G Parks
Journal of Turbomachinery 142 (2), 2020
Brownian motion in an N-scale periodic potential
AB Duncan, GA Pavliotis
arXiv preprint arXiv:1605.05854, 2016
A multiscale analysis of diffusions on rapidly varying surfaces
AB Duncan, CM Elliott, GA Pavliotis, AM Stuart
Journal of Nonlinear Science 25 (2), 389-449, 2015
Spatial Flow-Field Approximation Using Few Thermodynamic Measurements—Part I: Formulation and Area Averaging
P Seshadri, D Simpson, G Thorne, A Duncan, G Parks
Journal of Turbomachinery 142 (2), 2020
Manifold Learning for Accelerating Coarse-Grained Optimization
D Pozharskiy, NJ Wichrowski, AB Duncan, GA Pavliotis, IG Kevrekidis
arXiv preprint arXiv:2001.03518, 2020
Homogenization of lateral diffusion on a random surface
AB Duncan
Multiscale Modeling & Simulation 13 (4), 1478-1506, 2015
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Articles 1–20