Ömer Deniz Akyildiz

44 papers A* 3A 2Misc 1Journal 35Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
Diffusion Path Samplers via Sequential Monte Carlo.
CoRR
James Matthew Young, Paula Cordero-Encinar, Sebastian Reich, Andrew B. Duncan, Ömer Deniz Akyildiz
2025 J jnl
A Proximal Newton Adaptive Importance Sampler.
IEEE Signal Process. Lett.
Víctor Elvira, Émilie Chouzenoux, Ömer Deniz Akyildiz
2025 J jnl
Efficient Prior Calibration from Indirect Data.
SIAM J. Sci. Comput.
Ömer Deniz Akyildiz, Mark Girolami, Andrew M. Stuart, Arnaud Vadeboncoeur
2025 J jnl
Non-asymptotic Analysis of Diffusion Annealed Langevin Monte Carlo for Generative Modelling.
CoRR
Paula Cordero-Encinar, Ömer Deniz Akyildiz, Andrew B. Duncan
2025 J jnl
Nudging state-space models for Bayesian filtering under misspecified dynamics.
Stat. Comput.
Fabián González, Ömer Deniz Akyildiz, Dan Crisan, Joaquín Míguez
2025 J jnl
On diffusion posterior sampling via sequential Monte Carlo for zero-shot scaffolding of protein motifs.
Trans. Mach. Learn. Res.
James Matthew Young, Ömer Deniz Akyildiz
2025 J jnl
On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates.
Trans. Mach. Learn. Res.
Stefano Bruno, Ying Zhang, Dongyoung Lim, Ömer Deniz Akyildiz, Sotirios Sabanis
2025 A conf
Proximal Interacting Particle Langevin Algorithms.
UAI
Paula Cordero-Encinar, Francesca R. Crucinio, Ömer Deniz Akyildiz
2025 J jnl
Statistical Finite Elements via Interacting Particle Langevin Dynamics.
SIAM/ASA J. Uncertain. Quantification
Alex Glyn-Davies, Connor Duffin, Ieva Kazlauskaite, Mark Girolami, Ömer Deniz Akyildiz
2025 J jnl
Uniform-in-time convergence bounds for Persistent Contrastive Divergence Algorithms.
CoRR
Paul Felix Valsecchi Oliva, Ömer Deniz Akyildiz, Andrew B. Duncan
2024 J jnl
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling.
CoRR
Alex Glyn-Davies, Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami
2024 J jnl
Efficient Prior Calibration From Indirect Data.
CoRR
Ömer Deniz Akyildiz, Mark Girolami, Andrew M. Stuart, Arnaud Vadeboncoeur
2024 J jnl
Gaussian entropic optimal transport: Schrödinger bridges and the Sinkhorn algorithm.
CoRR
Ömer Deniz Akyildiz, Pierre Del Moral, Joaquín Míguez
2024 J jnl
Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization.
J. Mach. Learn. Res.
Ömer Deniz Akyildiz, Sotirios Sabanis
2024 J jnl
On Diffusion Posterior Sampling via Sequential Monte Carlo for Zero-Shot Scaffolding of Protein Motifs.
CoRR
James Matthew Young, Ömer Deniz Akyildiz
2024 J jnl
Sequential Discretization Schemes for a Class of Stochastic Differential Equations and their Application to Bayesian Filtering.
SIAM J. Numer. Anal.
Ömer Deniz Akyildiz, Dan Crisan, Joaquín Míguez
2024 J jnl
Tweedie Moment Projected Diffusions for Inverse Problems.
Trans. Mach. Learn. Res.
Benjamin Boys, Mark Girolami, Jakiw Pidstrigach, Sebastian Reich, Alan Mosca, Ömer Deniz Akyildiz
2024 J jnl
Φ-DVAE: Physics-informed dynamical variational autoencoders for unstructured data assimilation.
J. Comput. Phys.
Alex Glyn-Davies, Connor Duffin, Ömer Deniz Akyildiz, Mark Girolami
2023 J jnl
Fully probabilistic deep models for forward and inverse problems in parametric PDEs.
J. Comput. Phys.
Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami, Fehmi Cirak
2023 J jnl
Gradient-based adaptive importance samplers.
J. Frankl. Inst.
Víctor Elvira, Emilie Chouzenoux, Ömer Deniz Akyildiz, Luca Martino
2023 J jnl
On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates.
CoRR
Stefano Bruno, Ying Zhang, Dong-Young Lim, Ömer Deniz Akyildiz, Sotirios Sabanis
2023 A* conf
Random Grid Neural Processes for Parametric Partial Differential Equations.
ICML
Arnaud Vadeboncoeur, Ieva Kazlauskaite, Yanni Papandreou, Fehmi Cirak, Mark Girolami, Ömer Deniz Akyildiz
2023 J jnl
Random Grid Neural Processes for Parametric Partial Differential Equations.
CoRR
Arnaud Vadeboncoeur, Ieva Kazlauskaite, Yanni Papandreou, Fehmi Cirak, Mark Girolami, Ömer Deniz Akyildiz
2022 J jnl
$Φ$-DVAE: Learning Physically Interpretable Representations with Nonlinear Filtering.
CoRR
Alex Glyn-Davies, Connor Duffin, Ömer Deniz Akyildiz, Mark Girolami
2022 J jnl
Deep Probabilistic Models for Forward and Inverse Problems in Parametric PDEs.
CoRR
Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami, Fehmi Cirak
2022 J jnl
Statistical Finite Elements via Langevin Dynamics.
SIAM/ASA J. Uncertain. Quantification
Ömer Deniz Akyildiz, Connor Duffin, Sotirios Sabanis, Mark Girolami
2021 J jnl
Convergence rates for optimised adaptive importance samplers.
Stat. Comput.
Ömer Deniz Akyildiz, Joaquín Míguez
2021 A conf
Probabilistic Sequential Matrix Factorization.
AISTATS
Ömer Deniz Akyildiz, Gerrit J. J. van den Burg, Theodoros Damoulas, Mark F. J. Steel
2021 J jnl
Statistical Finite Elements via Langevin Dynamics.
CoRR
Ömer Deniz Akyildiz, Connor Duffin, Sotirios Sabanis, Mark Girolami
2020 A* conf
Generalised Bayesian Filtering via Sequential Monte Carlo.
NeurIPS
Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen
2020 J jnl
Generalized Bayesian Filtering via Sequential Monte Carlo.
CoRR
Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen
2020 J jnl
Nudging the particle filter.
Stat. Comput.
Ömer Deniz Akyildiz, Joaquín Míguez
2020 J jnl
Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization.
Stat. Comput.
Ömer Deniz Akyildiz, Dan Crisan, Joaquín Míguez
2020 A* conf
VarGrad: A Low-Variance Gradient Estimator for Variational Inference.
NeurIPS
Lorenz Richter, Ayman Boustati, Nikolas Nüsken, Francisco J. R. Ruiz, Ömer Deniz Akyildiz
2020 J jnl
VarGrad: A Low-Variance Gradient Estimator for Variational Inference.
CoRR
Lorenz Richter, Ayman Boustati, Nikolas Nüsken, Francisco J. R. Ruiz, Ömer Deniz Akyildiz
2019 J jnl
A Probabilistic Incremental Proximal Gradient Method.
IEEE Signal Process. Lett.
Ömer Deniz Akyildiz, Emilie Chouzenoux, Víctor Elvira, Joaquín Míguez
2019 J jnl
Dictionary filtering: a probabilistic approach to online matrix factorisation.
Signal Image Video Process.
Ömer Deniz Akyildiz, Joaquín Míguez
2019 J jnl
Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization.
CoRR
Ying Zhang, Ömer Deniz Akyildiz, Theo Damoulas, Sotirios Sabanis
2019 J jnl
Probabilistic sequential matrix factorization.
CoRR
Ömer Deniz Akyildiz, Theodoros Damoulas, Mark F. J. Steel
2018 Misc conf
The Incremental Proximal Method: A Probabilistic Perspective.
ICASSP
Ömer Deniz Akyildiz, Victor Elvira, Joaquín Míguez
2017 — conf
Adaptive noisy importance sampling for stochastic optimization.
CAMSAP
Ömer Deniz Akyildiz, Inés P. Mariño, Joaquín Míguez
2014 J jnl
Primal-dual algorithms for audio decomposition using mixed norms.
Signal Image Video Process.
Ilker Bayram, Ömer Deniz Akyildiz
2012 — conf
An analysis prior based decomposition method for audio signals.
EUSIPCO
Ömer Deniz Akyildiz, Ilker Bayram
2012 — conf
Signal decomposition via mixed-norm regularization.
SIU
Ömer Deniz Akyildiz, Ilker Bayram