ALEJANDRO PARADA-MAYORGA

Talks

  • “Algebraic Neural Networks: Stability to Deformations“. Invited talk, CIS department seminar at University of Delaware, 2023.
  • “Algebraic Neural Networks: Stability to Deformations“. Invited talk, CMSE department seminar at Michigan State University, 2023.
  • “Algebraic Neural Networks: Stability to Deformations“. Invited talk, ESE department seminar at University of Washington in St. Louis, 2023.
  • “Algebraic Neural Networks: Stability to Deformations“. Invited talk, ECE department seminar at University of Southern California, 2022.
  • “Algebraic Neural Networks: Stability to Deformations“. Invited talk, ECE department seminar at Michigan state university, 2022.
  • “Algebraic Neural Networks: Stability to Deformations“. Talk at the THEORINET Retreat.
  • “Algebraic Neural Networks: Stability to Deformations” (delivered by professor Alejandro Ribeiro). Seminar “Physics meets Machine Learning” at CERN. [video]
  • “Stability of Algebraic Neural Networks to Small Perturbations“. ICASSP 2021. [video]
  • Graphon Pooling in Graph Neural Networks. EUSIPCO January 19, 2020. [video]
  • Algebraic Neural Networks: Symmetry and Stability (delivered by professor Alejandro Ribeiro). Workshop on Equivariance and Data Augmentation at University of Pennsylvania, September 4, 2020. [Video]
  • Blue Noise and Optimal Sampling on Graphs (Dissertation Defense). Department of Electrical and Computer Engineering, University of Delaware, July 2019.
  • Blue-Noise Sampling on Graphs. 2019 Graph Signal Processing Workshop, MINNEAPOLIS, MN.
  • Optimal Sampling Sets in Cographs. 2019 IEEE Data Science Workshop, MINNEAPOLIS, MN.
  • Sampling of Graph Signals with Blue Noise Dithering. 2019 IEEE Data Science Workshop, MINNEAPOLIS, MN.
  • Blue Noise and Optimal Sampling on Graphs (Dissertation Proposal). Department of Electrical and Computer Engineering, University of Delaware, April 2019.
  • Introduction to Compressed Sensing. Seminar of the Computational Imaging and Data Science Group. Department of Electrical and Computer Engineering, University of Delaware, Fall 2015.
  • Compressed Sensing (Basics). Computational Imaging Seminar (ELEG 667), Fall 2016.
  • Compressed Sensing (Reconstruction Algorithms). Computational Imaging Seminar (ELEG 667), Fall 2016.

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