Pages that link to "Item:Q6158090"
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The following pages link to Scalable conditional deep inverse Rosenblatt transports using tensor trains and gradient-based dimension reduction (Q6158090):
Displaying 8 items.
- Deep Importance Sampling Using Tensor Trains with Application to a Priori and a Posteriori Rare Events (Q6189161) (← links)
- A low-rank solver for parameter estimation and uncertainty quantification in time-dependent systems of partial differential equations (Q6200967) (← links)
- Learning to solve Bayesian inverse problems: an amortized variational inference approach using Gaussian and flow guides (Q6560691) (← links)
- Conditional sampling with monotone GANs: from generative models to likelihood-free inference (Q6587628) (← links)
- Principal feature detection via \(\phi \)-Sobolev inequalities (Q6589581) (← links)
- Optimal experimental design: formulations and computations (Q6598420) (← links)
- Mini-workshop: Nonlinear approximation of high-dimensional functions in scientific computing. Abstracts from the mini-workshop held October 15--20, 2023 (Q6613392) (← links)
- On the representation and learning of monotone triangular transport maps (Q6659499) (← links)
