Luis Sa-Couto

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All published works

Action	Title	Year	Authors
+	Competitive learning to generate sparse representations for associative memory	2023	Luis Sa-Couto Andreas Wichert
+	Classification and generation of real-world data with an associative memory model	2023	Rodrigo Gabriel Simas Luis Sa-Couto Andreas Wichert
+	Using brain inspired principles to unsupervisedly learn good representations for visual pattern recognition	2022	Luis Sa-Couto Andreas Wichert
+	Multi-level Data Representation For Training Deep Helmholtz Machines	2022	Jose Miguel Ramos Luis Sa-Couto Andreas Wichert
+	Understanding the double descent curve in Machine Learning	2022	Luis Sa-Couto Jose Miguel Ramos Miguel Almeida Andreas Wichert
+	The smooth output assumption, and why deep networks are better than wide ones	2022	Luis Sa-Couto Jose Miguel Ramos Andreas Wichert
+	Classification and Generation of real-world data with an Associative Memory Model	2022	Rodrigo Gabriel Simas Luis Sa-Couto Andreas Wichert
+	Using brain inspired principles to unsupervisedly learn good representations for visual pattern recognition	2021	Luis Sa-Couto Andreas Wichert

Common Coauthors

Coauthor	Papers Together
Andreas Wichert	8
Jose Miguel Ramos	3
Rodrigo Gabriel Simas	2
Miguel Almeida	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	On the Information Storage Capacity of Local Learning Rules	1992	Günther Palm	1
+	High-Performance Neural Networks for Visual Object Classification	2011	Dan Cireşan Ueli Meier Jonatan Masci Luca Maria Gambardella Juergen Schmidhuber	1
+ PDF Chat	Sparse Neural Networks With Large Learning Diversity	2011	Vincent Gripon Claude Berrou	1
+	Categorical Reparameterization with Gumbel-Softmax	2016	Eric Jang Shixiang Gu Ben Poole	1
+	Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms	2017	Xiao Han Kashif Rasul Roland Vollgraf	1
+	How Can We Be So Dense? The Benefits of Using Highly Sparse Representations	2019	Subutai Ahmad Luiz Scheinkman	1
+	Biologically plausible deep learning — But how far can we go with shallow networks?	2019	Bernd Illing Wulfram Gerstner Johanni Brea	1
+	Continuous Online Sequence Learning with an Unsupervised Neural Network Model	2016	Yuwei Cui Subutai Ahmad Jeff Hawkins	1
+ PDF Chat	Learning representations in Bayesian Confidence Propagation neural networks	2020	Naresh Balaji Ravichandran Anders Lansner Pawel Herman	1
+	Using brain inspired principles to unsupervisedly learn good representations for visual pattern recognition	2022	Luis Sa-Couto Andreas Wichert	1
+	Dense Associative Memory for Pattern Recognition	2016	Dmitry Krotov J. J. Hopfield	1
+	Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution	2022	Anthony M. Zador Blake A. Richards Bence P. Ölveczky G. Sean Escola Yoshua Bengio Kwabena Boahen Matthew Botvinick Dmitri B. Chklovskii Anne K. Churchland Claudia Clopath	1