Jun 23, 2018 · The sparse manifold transform is an unsupervised and generative framework that explicitly and simultaneously models the sparse discreteness and ...

It turns non-linear transformations in the primary sensory signal space into linear interpolations in a representational embedding space while maintaining.

This paper presents an unsupervised learning method called sparse manifold transform for learning low-dimensional structures from data.

Sep 30, 2022 · Our approach leverages the sparse manifold transform, which unifies sparse coding, manifold learning, and slow feature analysis. With a one- ...

May 22, 2019 · The sparse manifold transform is an unsupervised and generative framework that explicitly and simultaneously models the sparse discreteness and ...

Apr 18, 2018 · Bruno Olshausen, UC Berkeley https://simons.berkeley.edu/talks/bruno-olshausen-4-18-18 Computational Theories of the Brain.

The sparse manifold transform is an unsupervised and generative framework that explicitly and simultaneously models the sparse discreteness and low-dimensional ...

Principles. Compute with chemistry. Compute directly with analog primitives. Combine analog and pulsatile processing. Sparsify. Send only what is needed.

Feb 1, 2023 · Our approach leverages the sparse manifold transform, which unifies sparse coding, manifold learning, and slow feature analysis. With a one- ...

The sparse manifold transform is an unsupervised and generative framework that explicitly and simultaneously models the sparse discreteness and low-dimensional ...