Luis Sa-Couto

Orcid: 0000-0001-9775-5079

According to our database1, Luis Sa-Couto authored at least 14 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Can a Hebbian-like learning rule be avoiding the curse of dimensionality in sparse distributed data?
Biol. Cybern., December, 2024

2023
Competitive learning to generate sparse representations for associative memory.
Neural Networks, November, 2023

Classification and generation of real-world data with an associative memory model.
Neurocomputing, September, 2023

Self-organizing maps on "what-where" codes towards fully unsupervised classification.
Biol. Cybern., June, 2023

2022
"What-Where" sparse distributed invariant representations of visual patterns.
Neural Comput. Appl., 2022

Using brain inspired principles to unsupervisedly learn good representations for visual pattern recognition.
Neurocomputing, 2022

The smooth output assumption, and why deep networks are better than wide ones.
CoRR, 2022

Understanding the double descent curve in Machine Learning.
CoRR, 2022

Multi-level Data Representation For Training Deep Helmholtz Machines.
CoRR, 2022

Multiple-Modality Associative Memory: a framework for Learning.
CoRR, 2022

2021
Simple Convolutional-Based Models: Are They Learning the Task or the Data?
Neural Comput., 2021

Machine Learning - A Journey to Deep Learning - with Exercises and Answers
WorldScientific, ISBN: 9789811234071, 2021

2020
Storing Object-Dependent Sparse Codes in a Willshaw Associative Network.
Neural Comput., 2020

2019
Attention Inspired Network: Steep learning curve in an invariant pattern recognition model.
Neural Networks, 2019


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