Fully probabilistic deep models for forward and inverse problems in parametric PDEs von Vadeboncoeur, Arnaud, Akyildiz, Ömer Deniz, Kazlauskaite, Ieva, Girolami, Mark, Cirak, Fehmi

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Nonasymptotic Estimates for Stochastic Gradient Langevin Dynamics Under Local Conditions in Nonconvex Optimization von Zhang, Ying, Akyildiz, Ömer Deniz, Damoulas, Theodoros, Sabanis, Sotirios

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Convergence rates for optimised adaptive importance samplers von Akyildiz, Ömer Deniz, Míguez, Joaquín

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Gradient-based adaptive importance samplers von Elvira, Víctor, Chouzenoux, Émilie, Akyildiz, Ömer Deniz, Martino, Luca

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Nudging the particle filter von Akyildiz, Ömer Deniz, Míguez, Joaquín

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Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization von Akyildiz, Ömer Deniz, Crisan, Dan, Míguez, Joaquín

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A Probabilistic Incremental Proximal Gradient Method von Akyildiz, Omer Deniz, Chouzenoux, Emilie, Elvira, Victor, Miguez, Joaquin

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Statistical Finite Elements via Langevin Dynamics von Akyildiz, Ömer Deniz, Duffin, Connor, Sabanis, Sotirios, Girolami, Mark

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Dictionary filtering: a probabilistic approach to online matrix factorisation von Akyildiz, Ömer Deniz, Míguez, Joaquín

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Global convergence of optimized adaptive importance samplers von Akyildiz, Ömer Deniz

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Global convergence of optimized adaptive importance samplers von Akyildiz, Ömer Deniz

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Adaptively Optimised Adaptive Importance Samplers von Perello, Carlos A. C. C, Akyildiz, Ömer Deniz

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Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization von Akyildiz, Ömer Deniz, Sabanis, Sotirios

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Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization von Akyildiz, Ömer Deniz, Sabanis, Sotirios

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Gradient-based Adaptive Importance Samplers von Elvira, Víctor, Chouzenoux, Emilie, Akyildiz, Ömer Deniz, Martino, Luca

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Convergence rates for optimised adaptive importance samplers von Akyildiz, Ömer Deniz, Míguez, Joaquín

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On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates von Bruno, Stefano, Zhang, Ying, Lim, Dong-Young, Akyildiz, Ömer Deniz, Sabanis, Sotirios

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Fully probabilistic deep models for forward and inverse problems in parametric PDEs von Vadeboncoeur, Arnaud, Akyildiz, Ömer Deniz, Kazlauskaite, Ieva, Girolami, Mark, Cirak, Fehmi

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Statistical Finite Elements via Langevin Dynamics von Akyildiz, Ömer Deniz, Duffin, Connor, Sabanis, Sotirios, Girolami, Mark

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Random Grid Neural Processes for Parametric Partial Differential Equations von Vadeboncoeur, Arnaud, Kazlauskaite, Ieva, Papandreou, Yanni, Cirak, Fehmi, Girolami, Mark, Akyildiz, Ömer Deniz

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