Silas Alberti
Silas Alberti
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Researches
Deep Learning Theory
Studying the effects of inductive biases on generalization of neural networks and kernel methods. Advised by Prof. Song Mei at UC Berkeley.
Silas Alberti
Last updated on Jan 18, 2022
Demo
Local Capsule Hierarchies
New architecture for learning deformable part-whole hierarchies. Collaboration with Domas Buracas and Nitish Dashora from Machine Learning at Berkeley, advised by Prof. Bruno Olshausen.
Silas Alberti
Last updated on Jan 18, 2022
Demo
Mathematical Foundations of Artificial Intelligence
Developing a new benchmark and studying new architectures for letting Graph Neural Networks detect directionality. Advised by Prof. Gitta Kutyniok and Dr. Ron Levie.
Silas Alberti
Last updated on Jan 18, 2022
Demo
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