Daniel Paulin - RankMe

19 papers A 1Journal 18

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Infinite-dimensional generative diffusions via Doob's h-transform. CoRR Thorben Pieper-Sethmacher, Daniel Paulin
2025	J	`jnl`	A Nonparametric Discrete Hawkes Model with a Collapsed Gaussian-Process Prior. CoRR Trinnhallen Brisley, Gordon Ross, Daniel Paulin
2025	A	`conf`	Sampling from Bayesian Neural Network Posteriors with Symmetric Minibatch Splitting Langevin Dynamics. AISTATS Daniel Paulin, Peter A. Whalley, Neil K. Chada, Benedict J. Leimkuhler
2024	J	`jnl`	Contraction and Convergence Rates for Discretized Kinetic Langevin Dynamics. SIAM J. Numer. Anal. Benedict J. Leimkuhler, Daniel Paulin, Peter A. Whalley
2024	J	`jnl`	Correction to "Wasserstein distance estimates for the distributions of numerical approximations to ergodic stochastic differential equations". CoRR Daniel Paulin, Peter A. Whalley
2024	J	`jnl`	Correction to "Wasserstein distance estimates for the distributions of numerical approximations to ergodic stochastic differential equations". J. Mach. Learn. Res. Daniel Paulin, Peter A. Whalley
2024	J	`jnl`	Randomized time Riemannian Manifold Hamiltonian Monte Carlo. Stat. Comput. Peter A. Whalley, Daniel Paulin, Benedict J. Leimkuhler
2024	J	`jnl`	Sampling from Bayesian Neural Network Posteriors with Symmetric Minibatch Splitting Langevin Dynamics. CoRR Daniel Paulin, Peter A. Whalley, Neil K. Chada, Benedict J. Leimkuhler
2023	J	`jnl`	Contraction Rate Estimates of Stochastic Gradient Kinetic Langevin Integrators. CoRR Benedict J. Leimkuhler, Daniel Paulin, Peter A. Whalley
2023	J	`jnl`	Contraction and Convergence Rates for Discretized Kinetic Langevin Dynamics. CoRR Benedict J. Leimkuhler, Daniel Paulin, Peter A. Whalley
2023	J	`jnl`	Unbiased Kinetic Langevin Monte Carlo with Inexact Gradients. CoRR Neil K. Chada, Benedict J. Leimkuhler, Daniel Paulin, Peter A. Whalley
2022	J	`jnl`	A 4D-Var method with flow-dependent background covariances for the shallow-water equations. Stat. Comput. Daniel Paulin, Ajay Jasra, Alexandros Beskos, Dan Crisan
2022	J	`jnl`	Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting. J. Mach. Learn. Res. Maxime Vono, Daniel Paulin, Arnaud Doucet
2021	J	`jnl`	Dual Space Preconditioning for Gradient Descent. SIAM J. Optim. Chris J. Maddison, Daniel Paulin, Yee Whye Teh, Arnaud Doucet
2021	J	`jnl`	On Mixing Times of Metropolized Algorithm With Optimization Step (MAO) : A New Framework. CoRR E. L. Mahdi Khribch, George Deligiannidis, Daniel Paulin
2019	J	`jnl`	Optimization Based Methods for Partially Observed Chaotic Systems. Found. Comput. Math. Daniel Paulin, Ajay Jasra, Dan Crisan, Alexandros Beskos
2018	J	`jnl`	Hamiltonian Descent Methods. CoRR Chris J. Maddison, Daniel Paulin, Yee Whye Teh, Brendan O'Donoghue, Arnaud Doucet
2016	J	`jnl`	Hypothesis testing for Markov chain Monte Carlo. Stat. Comput. Benjamin M. Gyori, Daniel Paulin
2014	J	`jnl`	Probabilistic verification of partially observable dynamical systems. CoRR Benjamin M. Gyori, Daniel Paulin, Sucheendra K. Palaniappan