14 citations · 27 across the 12 of their papers we have counts for
13 papers
Score Broadcast and Decorrelation: A General Framework for Broadcast-Based Credit Assignment
Mustafa Uzun, Mete Erdogan, Cengiz Pehlevan +1
We introduce Score Broadcast and Decorrelation (SBD), a principled framework for broadcast-based credit assignment for general families of differentiable losses. Error broadcast is…
Error Broadcast and Decorrelation as a Potential Artificial and Natural Learning Mechanism
Mete Erdogan, Cengiz Pehlevan, Alper T. Erdogan
We introduce Error Broadcast and Decorrelation (EBD), a novel learning framework for neural networks that addresses credit assignment by directly broadcasting output errors to indi…
Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry
Bariscan Bozkurt, Cengiz Pehlevan, Alper T Erdogan
The backpropagation algorithm has experienced remarkable success in training large-scale artificial neural networks; however, its biological plausibility has been strongly criticiz…
A Bayesian Perspective for Determinant Minimization Based Robust Structured Matrix Factorizatio
Gokcan Tatli, Alper T. Erdogan
We introduce a Bayesian perspective for the structured matrix factorization problem. The proposed framework provides a probabilistic interpretation for existing geometric methods b…
Correlative Information Maximization Based Biologically Plausible Neural Networks for Correlated Source Separation
Bariscan Bozkurt, Ates Isfendiyaroglu, Cengiz Pehlevan +1
The brain effortlessly extracts latent causes of stimuli, but how it does this at the network level remains unknown. Most prior attempts at this problem proposed neural networks th…
Self-Supervised Learning with an Information Maximization Criterion
Serdar Ozsoy, Shadi Hamdan, Sercan Ö. Arik +2
Self-supervised learning allows AI systems to learn effective representations from large amounts of data using tasks that do not require costly labeling. Mode collapse, i.e., the m…