15 citations · 17 across the 4 of their papers we have counts for
3 papers · 1 filter
Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes
Frank Schoeneman, Varun Chandola, Nils Napp +2
Scientific and engineering processes deliver massive high-dimensional data sets that are generated as non-linear transformations of an initial state and few process parameters. Map…
Error Metrics for Learning Reliable Manifolds from Streaming Data
Frank Schoeneman, Suchismit Mahapatra, Varun Chandola +2
Spectral dimensionality reduction is frequently used to identify low-dimensional structure in high-dimensional data. However, learning manifolds, especially from the streaming data…
On Optimality Conditions for Auto-Encoder Signal Recovery
Devansh Arpit, Yingbo Zhou, Hung Q. Ngo +2
Auto-Encoders are unsupervised models that aim to learn patterns from observed data by minimizing a reconstruction cost. The useful representations learned are often found to be sp…