Adrien Corenflos

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 20

Top Topics

Dynamical Systems

Gaussian Filter

Stochastic Differential Equations

Top Venues

J. Mach. Learn. Res.

Publications

Adrien Corenflos, Zheng Zhao, Simo Särkkä, Jens Sjölund, Thomas B. Schön
Conditioning diffusion models by explicit forward-backward bridging. CoRR (2024)
Yvann Le Fay, Simo Särkkä, Adrien Corenflos
Modelling pathwise uncertainty of Stochastic Differential Equations samplers via Probabilistic Numerics. CoRR (2024)
Alberto Cabezas, Adrien Corenflos, Junpeng Lao, Rémi Louf, Antoine Carnec, Kaustubh Chaudhari, Reuben Cohn-Gordon, Jeremie Coullon, Wei Deng, Sam Duffield, Gerardo Duràn-Martín, Marcin Elantkowski, Dan Foreman-Mackey, Michele Gregori, Carlos Iguaran, Ravin Kumar, Martin Lysy, Kevin Murphy, Juan Camilo Orduz, Karm Patel, Xi Wang, Rob Zinkov
BlackJAX: Composable Bayesian inference in JAX. CoRR (2024)
Sahel Iqbal, Adrien Corenflos, Simo Särkkä, Hany Abdulsamad
Nesting Particle Filters for Experimental Design in Dynamical Systems. CoRR (2024)
Adrien Corenflos, Simo Särkkä
Auxiliary MCMC and particle Gibbs samplers for parallelisable inference in latent dynamical systems. CoRR (2023)
Adrien Corenflos, Hany Abdulsamad
Variational Gaussian filtering via Wasserstein gradient flows. CoRR (2023)
Hany Abdulsamad, Sahel Iqbal, Adrien Corenflos, Simo Särkkä
Risk-Sensitive Stochastic Optimal Control as Rao-Blackwellized Markovian Score Climbing. CoRR (2023)
Adrien Corenflos, Matthew Sutton, Nicolas Chopin
Debiasing Piecewise Deterministic Markov Process samplers using couplings. CoRR (2023)
Nathanael Bosch, Adrien Corenflos, Fatemeh Yaghoobi, Filip Tronarp, Philipp Hennig, Simo Särkkä
Parallel-in-Time Probabilistic Numerical ODE Solvers. CoRR (2023)
Adrien Corenflos, Hany Abdulsamad
Variational Gaussian Filtering via Wasserstein Gradient Flows. EUSIPCO (2023)
Adrien Corenflos, Nicolas Chopin, Simo Särkkä
De-Sequentialized Monte Carlo: a parallel-in-time particle smoother. CoRR (2022)
Adrien Corenflos, Nicolas Chopin, Simo Särkkä
De-Sequentialized Monte Carlo: a parallel-in-time particle smoother. J. Mach. Learn. Res. 23 (2022)
Adrien Corenflos, Zheng Zhao, Simo Särkkä
Temporal Gaussian Process Regression in Logarithmic Time. FUSION (2022)
Fatemeh Yaghoobi, Adrien Corenflos, Sakira Hassan, Simo Särkkä
Parallel square-root statistical linear regression for inference in nonlinear state space models. CoRR (2022)
Fatemeh Yaghoobi, Adrien Corenflos, Sakira Hassan, Simo Särkkä
Parallel Iterated Extended and Sigma-Point Kalman Smoothers. ICASSP (2021)
Adrien Corenflos, James Thornton, Arnaud Doucet, George Deligiannidis
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport. CoRR (2021)
Adrien Corenflos, James Thornton, George Deligiannidis, Arnaud Doucet
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport. ICML (2021)
Rémi Flamary, Nicolas Courty, Alexandre Gramfort, Mokhtar Z. Alaya, Aurélie Boisbunon, Stanislas Chambon, Laetitia Chapel, Adrien Corenflos, Kilian Fatras, Nemo Fournier, Léo Gautheron, Nathalie T. H. Gayraud, Hicham Janati, Alain Rakotomamonjy, Ievgen Redko, Antoine Rolet, Antony Schutz, Vivien Seguy, Danica J. Sutherland, Romain Tavenard, Alexander Tong, Titouan Vayer
POT: Python Optimal Transport. J. Mach. Learn. Res. 22 (2021)
Adrien Corenflos, Zheng Zhao, Simo Särkkä
Gaussian Process Regression in Logarithmic Time. CoRR (2021)
Fatemeh Yaghoobi, Adrien Corenflos, Sakira Hassan, Simo Särkkä
Parallel Iterated Extended and Sigma-point Kalman Smoothers. CoRR (2021)