Ömer Deniz Akyildiz

According to our database, Ömer Deniz Akyildiz authored at least 30 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Sequential Discretization Schemes for a Class of Stochastic Differential Equations and their Application to Bayesian Filtering.

Ömer Deniz Akyildiz, Dan Crisan, Joaquín Míguez

SIAM J. Numer. Anal., 2024

Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization.

Ömer Deniz Akyildiz, Sotirios Sabanis

J. Mach. Learn. Res., 2024

Φ-DVAE: Physics-informed dynamical variational autoencoders for unstructured data assimilation.

Alex Glyn-Davies, Connor Duffin, Ömer Deniz Akyildiz, Mark Girolami

J. Comput. Phys., 2024

Gaussian entropic optimal transport: Schrödinger bridges and the Sinkhorn algorithm.

Ömer Deniz Akyildiz, Pierre Del Moral, Joaquín Míguez

CoRR, 2024

On Diffusion Posterior Sampling via Sequential Monte Carlo for Zero-Shot Scaffolding of Protein Motifs.

James Matthew Young, Ömer Deniz Akyildiz

CoRR, 2024

A Primer on Variational Inference for Physics-Informed Deep Generative Modelling.

Alex Glyn-Davies, Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami

CoRR, 2024

Efficient Prior Calibration From Indirect Data.

Ömer Deniz Akyildiz, Mark Girolami, Andrew M. Stuart, Arnaud Vadeboncoeur

CoRR, 2024

2023

Fully probabilistic deep models for forward and inverse problems in parametric PDEs.

Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami, Fehmi Cirak

J. Comput. Phys., October, 2023

Gradient-based adaptive importance samplers.

Víctor Elvira, Emilie Chouzenoux, Ömer Deniz Akyildiz, Luca Martino

J. Frankl. Inst., September, 2023

On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates.

Stefano Bruno, Ying Zhang, Dong-Young Lim, Ömer Deniz Akyildiz, Sotirios Sabanis

CoRR, 2023

Random Grid Neural Processes for Parametric Partial Differential Equations.

Arnaud Vadeboncoeur, Ieva Kazlauskaite, Yanni Papandreou, Fehmi Cirak, Mark Girolami, Ömer Deniz Akyildiz

Proceedings of the International Conference on Machine Learning, 2023

2022

Statistical Finite Elements via Langevin Dynamics.

Ömer Deniz Akyildiz, Connor Duffin, Sotirios Sabanis, Mark Girolami

SIAM/ASA J. Uncertain. Quantification, 2022

$Φ$-DVAE: Learning Physically Interpretable Representations with Nonlinear Filtering.

Alex Glyn-Davies, Connor Duffin, Ömer Deniz Akyildiz, Mark Girolami

CoRR, 2022

Deep Probabilistic Models for Forward and Inverse Problems in Parametric PDEs.

Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami, Fehmi Cirak

CoRR, 2022

2021

Convergence rates for optimised adaptive importance samplers.

Ömer Deniz Akyildiz, Joaquín Míguez

Stat. Comput., 2021

Probabilistic Sequential Matrix Factorization.

Ömer Deniz Akyildiz, Gerrit J. J. van den Burg, Theodoros Damoulas, Mark F. J. Steel

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Nudging the particle filter.

Ömer Deniz Akyildiz, Joaquín Míguez

Stat. Comput., 2020

Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization.

Ömer Deniz Akyildiz, Dan Crisan, Joaquín Míguez

Stat. Comput., 2020

Generalized Bayesian Filtering via Sequential Monte Carlo.

Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen

CoRR, 2020

VarGrad: A Low-Variance Gradient Estimator for Variational Inference.

Lorenz Richter, Ayman Boustati, Nikolas Nüsken, Francisco J. R. Ruiz, Ömer Deniz Akyildiz

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Generalised Bayesian Filtering via Sequential Monte Carlo.

Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

A Probabilistic Incremental Proximal Gradient Method.

Ömer Deniz Akyildiz, Emilie Chouzenoux, Víctor Elvira, Joaquín Míguez

IEEE Signal Process. Lett., 2019

Dictionary filtering: a probabilistic approach to online matrix factorisation.

Ömer Deniz Akyildiz, Joaquín Míguez

Signal Image Video Process., 2019

Probabilistic sequential matrix factorization.

Ömer Deniz Akyildiz, Theodoros Damoulas, Mark F. J. Steel

CoRR, 2019

Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization.

Ying Zhang, Ömer Deniz Akyildiz, Theo Damoulas, Sotirios Sabanis

CoRR, 2019

2018

The Incremental Proximal Method: A Probabilistic Perspective.

Ömer Deniz Akyildiz, Victor Elvira, Joaquín Míguez

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017

Adaptive noisy importance sampling for stochastic optimization.

Ömer Deniz Akyildiz, Inés P. Mariño, Joaquín Míguez

Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

2014

Primal-dual algorithms for audio decomposition using mixed norms.

Ilker Bayram, Ömer Deniz Akyildiz

Signal Image Video Process., 2014

2012

Signal decomposition via mixed-norm regularization.

Ömer Deniz Akyildiz, Ilker Bayram

Proceedings of the 20th Signal Processing and Communications Applications Conference, 2012

An analysis prior based decomposition method for audio signals.

Ömer Deniz Akyildiz, Ilker Bayram

Proceedings of the 20th European Signal Processing Conference, 2012