31 citations · 31 across the 4 of their papers we have counts for
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stat.CO2022
Gradient-based Adaptive Importance Samplers
Víctor Elvira, Emilie Chouzenoux, Ömer Deniz Akyildiz +1
Importance sampling (IS) is a powerful Monte Carlo methodology for the approximation of intractable integrals, very often involving a target probability density function. The perfo…
stat.ML2022★ 31 cited
Fully probabilistic deep models for forward and inverse problems in parametric PDEs
Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite +2
We introduce a physics-driven deep latent variable model (PDDLVM) to learn simultaneously parameter-to-solution (forward) and solution-to-parameter (inverse) maps of parametric par…