Alejandro Parada-Mayorga, Ph.D.

RKHS Representation of Algebraic Convolutional Filters with Integral Operators Integral operators play a central role in signal processing, underpinning classical convolution, and filtering on continuous network models such as graphons. While these operators are traditionally an...

A new preprint is out: "RKHS Representation of Algebraic Convolutional Filters with Integral Operators", arxiv.org/abs/2602.19094

"Sampling and uniqueness sets in graphon signal processing" and "Convolutional Filtering with RKHS Algebras". Joint work with Alejandro Ribeiro. CU Denver College of Engineering, Design, and Computing, University of Pennsylvania

I'm presenting at the 2026 IEEE International Conference on Acoustics, Speech, and Signal Processing, join me Register now

I'm presenting two papers at the 2026 IEEE International Conference on Acoustics, Speech, and Signal Processing in Barcelona. Learn more! invt.io/1bxbf87rq3h

Some of the best works questioning the necessity of probabilistic models of uncertainty come from the world of mathematical finance: Fischer Black's paper on noise, Hans Föllmer, Vladimir Vovk. Machine learning should be more like mathematical finance.

Is this coffeeshop located in Champaign, IL?

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This one is even better if you use a fountain pen, Leuchtturm can bleed when using certain pens:
www.amazon.com/Life-Noble-N...

Our work “DiffKillR: Killing and Recreating Diffeomorphisms for Cell Annotation in Dense Microscopy Images” will be presented at IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 2025 August 31-September 3, Istanbul/Turkey. lnkd.in/eu7uyh7E

New Proofs Probe the Limits of Mathematical Truth | Quanta Magazine By proving a broader version of Hilbert’s famous 10th problem, two groups of mathematicians have expanded the realm of mathematical unknowability.

What can’t we know? This question haunts all corners of math. Now, two independent proofs of a broader version of Hilbert’s famous 10th problem have expanded the bounds of mathematical unknowability. Joseph Howlett reports:
www.quantamagazine.org/new-proofs-p...

Alejandro Parada-Mayorga, Algebraic Neural Networks: Stability to Deformations, 2024.09.24 YouTube video by CodEx Seminar

www.youtube.com/watch?v=o-bm...

Convolutional Filtering with RKHS Algebras In this paper, we develop a generalized theory of convolutional signal processing and neural networks for Reproducing Kernel Hilbert Spaces (RKHS). Leveraging the theory of algebraic signal processing...

arxiv.org/abs/2411.01341

Convolutional Filtering with RKHS Algebras In this paper, we develop a generalized theory of convolutional signal processing and neural networks for Reproducing Kernel Hilbert Spaces (RKHS). Leveraging the theory of algebraic signal processing...

New paper is out: "Convolutional Filtering with RKHS Algebras"

arxiv.org/abs/2411.01341