no code implementations • 30 Jun 2022 • Naresh Balaji Ravichandran, Anders Lansner, Pawel Herman
We approach this problem by combining a recurrent attractor network with a feedforward network that learns distributed representations using an unsupervised Hebbian-Bayesian learning rule.
no code implementations • 29 Jun 2021 • Naresh Balaji Ravichandran, Anders Lansner, Pawel Herman
Learning internal representations from data using no or few labels is useful for machine learning research, as it allows using massive amounts of unlabeled data.
1 code implementation • 9 Jun 2021 • Artur Podobas, Martin Svedin, Steven W. D. Chien, Ivy B. Peng, Naresh Balaji Ravichandran, Pawel Herman, Anders Lansner, Stefano Markidis
The modern deep learning method based on backpropagation has surged in popularity and has been used in multiple domains and application areas.
no code implementations • 6 May 2020 • Naresh Balaji Ravichandran, Anders Lansner, Pawel Herman
Unsupervised learning of hidden representations has been one of the most vibrant research directions in machine learning in recent years.
no code implementations • 27 Mar 2020 • Naresh Balaji Ravichandran, Anders Lansner, Pawel Herman
Unsupervised learning of hierarchical representations has been one of the most vibrant research directions in deep learning during recent years.