For a complete up-to-date list, check out my Google Scholar
We present a probabilistic framework for both
(i) determining the initial settings of kernel adaptive filters
(KAFs) and (ii) constructing fully-adaptive KAFs whereby in
addition to weights and dictionaries, kernel parameters are learnt
* These authors contributed equally
We developed a tool integrating different visualizations and algorithms in order to make the geological resource assessment process faster. We focused mainly in three aspects: a software responsive in terms of usability, a software with high performance capabilities in terms of parallel and distributed execution of geostatistical algorithms, and a software that allows to re-execute the same resource assessment task in different time scales with little overhead for the user.
Undergraduate Thesis (spanish)
The main contribution of this work is a review of Probabilistic Graphical Model literature and its applications on Computer Vision tasks, specifically Semantic Segmentation. In particular, this work serves as a guide on how to model images as undirected graphs and use a general purpose solver for optimizing the outputs of a classification model without additional data.
Presentations / Teaching Material
The following presentations were prepared for class lectures and reading groups.
I have been Teaching Assistant for the following courses at Universidad de Chile
- Probabilistic Machine Learning (2016)
- Bayesian Automatic Learning (2016)
- Robotics (2015)
- Information Technologies (2015)
- Communication Principles (2014)
- Analysis and Design of Electrical Circuits
Most of my work in these courses consisted on developing teaching materials, evaluations and solution guides. For Machine Learning related courses, I had a major role in designing the course syllabus and class slides with the professor (Bayesian Automatic Learning), as well as creating programming assignments for the students (Probabilistic Machine Learning).
Independent work I did after finishing my undergraduate thesis, mostly for fun