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GSoC 2019 Final Evaluation

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Review of the things done during GSoC 2019.

The coding period is coming to an end

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In this post we will reflect on what we been doing for GSoC and some of the difficulties that arose.

Posterior inference in Bayesian Additive Regression Trees

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In this post we will show how the posterior inference in BART is performed.

BART’s tree structure implementation

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In this post we will show the implementation for the tree structure of BART.

Introduction to Bayesian Additive Regression Trees

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In this post we will delve into the theory of Bayesian Additive Regression Trees (BART).

Coding period begins

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At this point the bonding period already ended and we are in the middle of the coding period. In this post I will tell you how things are going.

Accepted to the Google Summer of Code 2019

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print('Hello World!')


Learning When to Classify for Early Text Classification

Published in Argentine Congress of Computer Science, 2017

This paper presents a simple framework for early text classification.

Recommended citation: Loyola, J. M., Errecalde, M. L., Escalante, H. J., & y Gomez, M. M. (2017, October). Learning When to Classify for Early Text Classification. In Argentine Congress of Computer Science (pp. 24-34). Springer, Cham. http://hdl.handle.net/10915/63498

Classification of RNA backbone conformation into rotamers using 13C′ chemical shifts How far we can go?

Published in PeerJ, 2019

In the present work, we use the ribose experimental and theoretical 13C′ chemical shifts data and machine learning methods to classify RNA backbone conformations into rotamers and families of rotamers.

Recommended citation: Icazatti, A. A., Loyola, J. M., Szleifer, I., Vila, J. A., & Martin, O. A. (2019). Classification of RNA backbone conformation into rotamers using 13C′ chemical shifts: exploring how far we can go. PeerJ 7:e7904 https://doi.org/10.7717/peerj.7904 https://peerj.com/articles/7904.pdf

Introducción al Aprendizaje Automático

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I gave a talk at the PyData San Luis MeetUp titled “Introducción al Aprendizaje Automático” (in english, “Introduction to Machine Learning”.

Learning When to Classify for Early Text Classification

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I presented the paper “Learning When to Classify for Early Text Classification” in the XVIII Workshop of Intelligent Agents and Systems of the XXII Argentine Congress of Computer Science.

Introducción a la computación científica con Python

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I gave a short talk titled “Búsqueda de Patrones en Texto” (in english, “Search for patterns in text”) as part of a PyData San Luis MeetUp, “Introducción a la computación científica con Python” (in english, “Introduction to scientific computing with Python”).

Deep Learning

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I gave a talk titled “Deep Learning” as part of the I Jornadas de Informática in the Informatics Department of the National University of San Luis”. The slides are available here.

Introducción al Aprendizaje Profundo

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I gave a lightning talk titled “Introducción al Aprendizaje Profundo” (in english, “Introduction to Deep Learning”) at the Taller Argentino de Computación Científica. The slides are available here.

Lógica para Computación (First Semester 2019)

Undergraduate course, National University of San Luis, Informatics Department, 2019

Teaching assistant

Estructura de Datos y Algoritmos (Second Semester 2019)

Undergraduate course, National University of San Luis, Informatics Department, 2019

Teaching assistant