Ömer Deniz Akyildiz

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 26

Top Topics

Importance Sampling

Stochastic Gradient

Sequential Monte Carlo

Bayesian Filtering

Top Venues

J. Comput. Phys.

Signal Image Video Process.

Publications

Ömer Deniz Akyildiz, Mark Girolami, Andrew M. Stuart, Arnaud Vadeboncoeur
Efficient Prior Calibration From Indirect Data. CoRR (2024)
Alex Glyn-Davies, Connor Duffin, Ömer Deniz Akyildiz, Mark Girolami
Φ-DVAE: Physics-informed dynamical variational autoencoders for unstructured data assimilation. J. Comput. Phys. 515 (2024)
Ömer Deniz Akyildiz, Dan Crisan, Joaquín Míguez
Sequential Discretization Schemes for a Class of Stochastic Differential Equations and their Application to Bayesian Filtering. SIAM J. Numer. Anal. 62 (2) (2024)
Arnaud Vadeboncoeur, Ieva Kazlauskaite, Yanni Papandreou, Fehmi Cirak, Mark Girolami, Ömer Deniz Akyildiz
Random Grid Neural Processes for Parametric Partial Differential Equations. CoRR (2023)
Arnaud Vadeboncoeur, Ieva Kazlauskaite, Yanni Papandreou, Fehmi Cirak, Mark Girolami, Ömer Deniz Akyildiz
Random Grid Neural Processes for Parametric Partial Differential Equations. ICML (2023)
Víctor Elvira, Émilie Chouzenoux, Ömer Deniz Akyildiz, Luca Martino
Gradient-based adaptive importance samplers. J. Frankl. Inst. 360 (13) (2023)
Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami, Fehmi Cirak
Fully probabilistic deep models for forward and inverse problems in parametric PDEs. J. Comput. Phys. 491 (2023)
Stefano Bruno, Ying Zhang, Dong-Young Lim, Ömer Deniz Akyildiz, Sotirios Sabanis
On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates. CoRR (2023)
Alex Glyn-Davies, Connor Duffin, Ömer Deniz Akyildiz, Mark Girolami
$Φ$-DVAE: Learning Physically Interpretable Representations with Nonlinear Filtering. CoRR (2022)
Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami, Fehmi Cirak
Deep Probabilistic Models for Forward and Inverse Problems in Parametric PDEs. CoRR (2022)
Ömer Deniz Akyildiz, Connor Duffin, Sotirios Sabanis, Mark Girolami
Statistical Finite Elements via Langevin Dynamics. SIAM/ASA J. Uncertain. Quantification 10 (4) (2022)
Ömer Deniz Akyildiz, Joaquín Míguez
Convergence rates for optimised adaptive importance samplers. Stat. Comput. 31 (2) (2021)
Ömer Deniz Akyildiz, Gerrit van den Burg, Theodoros Damoulas, Mark F. J. Steel
Probabilistic Sequential Matrix Factorization. AISTATS (2021)
Ömer Deniz Akyildiz, Connor Duffin, Sotirios Sabanis, Mark Girolami
Statistical Finite Elements via Langevin Dynamics. CoRR (2021)
Lorenz Richter, Ayman Boustati, Nikolas Nüsken, Francisco J. R. Ruiz, Ömer Deniz Akyildiz
VarGrad: A Low-Variance Gradient Estimator for Variational Inference. NeurIPS (2020)
Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen
Generalised Bayesian Filtering via Sequential Monte Carlo. NeurIPS (2020)
Lorenz Richter, Ayman Boustati, Nikolas Nüsken, Francisco J. R. Ruiz, Ömer Deniz Akyildiz
VarGrad: A Low-Variance Gradient Estimator for Variational Inference. CoRR (2020)
Ömer Deniz Akyildiz, Dan Crisan, Joaquín Míguez
Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization. Stat. Comput. 30 (6) (2020)
Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen
Generalized Bayesian Filtering via Sequential Monte Carlo. CoRR (2020)
Ömer Deniz Akyildiz, Joaquín Míguez
Nudging the particle filter. Stat. Comput. 30 (2) (2020)
Ying Zhang, Ömer Deniz Akyildiz, Theo Damoulas, Sotirios Sabanis
Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization. CoRR (2019)
Ömer Deniz Akyildiz, Theodoros Damoulas, Mark F. J. Steel
Probabilistic sequential matrix factorization. CoRR (2019)
Ömer Deniz Akyildiz, Joaquín Míguez
Dictionary filtering: a probabilistic approach to online matrix factorisation. Signal Image Video Process. 13 (4) (2019)
Ömer Deniz Akyildiz, Émilie Chouzenoux, Víctor Elvira, Joaquín Míguez
A Probabilistic Incremental Proximal Gradient Method. IEEE Signal Process. Lett. 26 (8) (2019)
Ömer Deniz Akyildiz, Victor Elvira, Joaquín Míguez
The Incremental Proximal Method: A Probabilistic Perspective. ICASSP (2018)
Ömer Deniz Akyildiz, Inés P. Mariño, Joaquín Míguez
Adaptive noisy importance sampling for stochastic optimization. CAMSAP (2017)
Ilker Bayram, Ömer Deniz Akyildiz
Primal-dual algorithms for audio decomposition using mixed norms. Signal Image Video Process. 8 (1) (2014)
Ömer Deniz Akyildiz, Ilker Bayram
Signal decomposition via mixed-norm regularization. SIU (2012)
Ömer Deniz Akyildiz, Ilker Bayram
An analysis prior based decomposition method for audio signals. EUSIPCO (2012)