25 citations · 49 across the 14 of their papers we have counts for
3 papers · 1 filter
Enabling Probabilistic Learning on Manifolds through Double Diffusion Maps
Dimitris G Giovanis, Nikolaos Evangelou, Ioannis G Kevrekidis +1
We present a generative learning framework for probabilistic sampling based on an extension of the Probabilistic Learning on Manifolds (PLoM) approach, which is designed to generat…
Double Diffusion Maps and their Latent Harmonics for Scientific Computations in Latent Space
Nikolaos Evangelou, Felix Dietrich, Eliodoro Chiavazzo +3
We introduce a data-driven approach to building reduced dynamical models through manifold learning; the reduced latent space is discovered using Diffusion Maps (a manifold learning…
Initializing LSTM internal states via manifold learning
Felix P. Kemeth, Tom Bertalan, Nikolaos Evangelou +3
We present an approach, based on learning an intrinsic data manifold, for the initialization of the internal state values of LSTM recurrent neural networks, ensuring consistency wi…