16 citations · 40 across the 18 of their papers we have counts for
7 papers · 1 filter
Diffusion Path Samplers via Sequential Monte Carlo
James Matthew Young, Paula Cordero-Encinar, Sebastian Reich +2
We develop diffusion-based samplers for target distributions known up to a normalising constant. To this end, we rely on the well-known diffusion path that smoothly interpolates be…
Non-asymptotic Analysis of Diffusion Annealed Langevin Monte Carlo for Generative Modelling
Paula Cordero-Encinar, O. Deniz Akyildiz, Andrew B. Duncan
We investigate the theoretical properties of general diffusion (interpolation) paths and their Langevin Monte Carlo implementation, referred to as diffusion annealed Langevin Monte…
Gaussian entropic optimal transport: Schrödinger bridges and the Sinkhorn algorithm
O. Deniz Akyildiz, Pierre Del Moral, Joaquín Miguez
Entropic optimal transport problems are regularized versions of optimal transport problems. These models play an increasingly important role in machine learning and generative mode…
Efficient Prior Calibration From Indirect Data
O. Deniz Akyildiz, Mark Girolami, Andrew M. Stuart +1
Bayesian inversion is central to the quantification of uncertainty within problems arising from numerous applications in science and engineering. To formulate the approach, four in…
-DVAE: Physics-Informed Dynamical Variational Autoencoders for Unstructured Data Assimilation
Alex Glyn-Davies, Connor Duffin, Ö. Deniz Akyildiz +1
Incorporating unstructured data into physical models is a challenging problem that is emerging in data assimilation. Traditional approaches focus on well-defined observation operat…
VarGrad: A Low-Variance Gradient Estimator for Variational Inference
Lorenz Richter, Ayman Boustati, Nikolas Nüsken +2
We analyse the properties of an unbiased gradient estimator of the ELBO for variational inference, based on the score function method with leave-one-out control variates. We show t…
Matrix Factorisation with Linear Filters
Ömer Deniz Akyıldız
This text investigates relations between two well-known family of algorithms, matrix factorisations and recursive linear filters, by describing a probabilistic model in which appro…