We present a sub-symbolic computational model for effecting knowledge re-representation and insight. Given a set of data, manifold learning is used to automatically organize the d...
Background: Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the gen...
Jacek Sroka, Lukasz Bieniasz-Krzywiec, Szymon Gwoz...
We review some results about the computational power of several computational models. Considered models have in common to be related to continuous dynamical systems. 1 Dynamical Sy...
The Machine Learning and Pattern Recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization pro...
When an observer moves in a 3D static scene, the motion field depends on the depth of the visible objects and on the observer’s instantaneous translation and rotation. By compu...