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2020 – today
- 2024
[j7]Peter A. Whalley, Daniel Paulin, Benedict J. Leimkuhler:
Randomized time Riemannian Manifold Hamiltonian Monte Carlo. Stat. Comput. 34(1): 48 (2024)- [j6]Benedict J. Leimkuhler
, Daniel Paulin, Peter A. Whalley:
Contraction and Convergence Rates for Discretized Kinetic Langevin Dynamics. SIAM J. Numer. Anal. 62(3): 1226-1258 (2024) - [i8]Daniel Paulin, Peter A. Whalley:
Correction to "Wasserstein distance estimates for the distributions of numerical approximations to ergodic stochastic differential equations". CoRR abs/2402.08711 (2024) - [i7]Daniel Paulin, Peter A. Whalley, Neil K. Chada, Benedict J. Leimkuhler:
Sampling from Bayesian Neural Network Posteriors with Symmetric Minibatch Splitting Langevin Dynamics. CoRR abs/2410.19780 (2024) - 2023
- [i6]Benedict J. Leimkuhler, Daniel Paulin, Peter A. Whalley:
Contraction and Convergence Rates for Discretized Kinetic Langevin Dynamics. CoRR abs/2302.10684 (2023) - [i5]Benedict J. Leimkuhler, Daniel Paulin, Peter A. Whalley:
Contraction Rate Estimates of Stochastic Gradient Kinetic Langevin Integrators. CoRR abs/2306.08592 (2023) - [i4]Neil K. Chada, Benedict J. Leimkuhler, Daniel Paulin, Peter A. Whalley:
Unbiased Kinetic Langevin Monte Carlo with Inexact Gradients. CoRR abs/2311.05025 (2023) - 2022
- [j5]Maxime Vono, Daniel Paulin, Arnaud Doucet:
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting. J. Mach. Learn. Res. 23: 25:1-25:69 (2022) - [j4]Daniel Paulin, Ajay Jasra, Alexandros Beskos, Dan Crisan:
A 4D-Var method with flow-dependent background covariances for the shallow-water equations. Stat. Comput. 32(4): 65 (2022) - 2021
- [j3]Chris J. Maddison, Daniel Paulin, Yee Whye Teh, Arnaud Doucet:
Dual Space Preconditioning for Gradient Descent. SIAM J. Optim. 31(1): 991-1016 (2021) - [i3]E. L. Mahdi Khribch, George Deligiannidis, Daniel Paulin:
On Mixing Times of Metropolized Algorithm With Optimization Step (MAO) : A New Framework. CoRR abs/2112.00565 (2021)
2010 – 2019
- 2019
- [j2]Daniel Paulin, Ajay Jasra, Dan Crisan, Alexandros Beskos:
Optimization Based Methods for Partially Observed Chaotic Systems. Found. Comput. Math. 19(3): 485-559 (2019) - 2018
- [i2]Chris J. Maddison, Daniel Paulin, Yee Whye Teh, Brendan O'Donoghue, Arnaud Doucet:
Hamiltonian Descent Methods. CoRR abs/1809.05042 (2018) - 2016
- [j1]Benjamin M. Gyori, Daniel Paulin:
Hypothesis testing for Markov chain Monte Carlo. Stat. Comput. 26(6): 1281-1292 (2016) - 2014
- [i1]Benjamin M. Gyori, Daniel Paulin, Sucheendra K. Palaniappan:
Probabilistic verification of partially observable dynamical systems. CoRR abs/1411.0976 (2014)
Coauthor Index
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