Detection of Anomalies in Large Datasets Using an Active Learning Scheme Based on Dirichlet Distributions. - Karim Pichara; Alvaro Soto; Anita Araneda (IBERAMIA, 2008)

Active learning and subspace clustering for anomaly detection. - Karim Pichara; Alvaro Soto (Intell. Data Anal., 2011)

Automatic Classification of Variable Stars in Catalogs with missing data. - Karim Pichara; Pavlos Protopapas (CoRR, 2013)

Supervised detection of anomalous light-curves in massive astronomical catalogs. - Isadora nun; Karim Pichara; Pavlos Protopapas; Dae-Won Kim (CoRR, 2014)

Local feature selection using Gaussian process regression. - Karim Pichara; Alvaro Soto (Intell. Data Anal., 2014)

Clustering Based Feature Learning on Variable Stars. - Cristóbal Mackenzie; Karim Pichara; Pavlos Protopapas (CoRR, 2016)

Astronomical data analysis software and systems. - Mauricio Solar; Amelia Bayo; Nuria P. F. Lorente; Karim Pichara (Astron. Comput., 2018)

Deep multi-survey classification of variable stars. - Carlos Aguirre; Karim Pichara; Ignacio Becker (CoRR, 2018)

Centralized student performance prediction in large courses based on low-cost variables in an institutional context. - Augusto Sandoval; Carlos Gonzalez; Rosa Alarcón; Karim Pichara; Maximiliano Montenegro (Internet High. Educ., 2018)

Understanding Learning Resources Metadata for Primary and Secondary Education. - Monserrat Peralta; Rosa Alarcón; Karim Pichara; Tomas Mery; Felipe Cano; Jorge Bozo (IEEE Trans. Learn. Technol., 2018)

An Algorithm for the Visualization of Relevant Patterns in Astronomical Light Curves. - Christian Pieringer; Karim Pichara; Márcio Catelán; Pavlos Protopapas (CoRR, 2019)

An Information Theory Approach on Deciding Spectroscopic Follow Ups. - Javiera Astudillo; Pavlos Protopapas; Karim Pichara; Pablo Huijse (CoRR, 2019)

Streaming Classification of Variable Stars. - Lukas Zorich; Karim Pichara; Pavlos Protopapas (CoRR, 2019)

Scalable End-to-end Recurrent Neural Network for Variable star classification. - Ignacio Becker; Karim Pichara; Márcio Catelán; Pavlos Protopapas; Carlos Aguirre; Fatemeh Nikzat (CoRR, 2020)

Classifying CMB time-ordered data through deep neural networks. - Felipe Rojas; Loïc Maurin; Rolando Dünner; Karim Pichara (CoRR, 2020)

Informative Bayesian model selection for RR Lyrae star classifiers. - Francisco Pérez-Galarce; Karim Pichara; Pablo Huijse; Márcio Catelán; Domingo Mery (CoRR, 2021)

Uncertainty Quantification in Neural Differential Equations. - Olga Graf; Pablo Flores; Pavlos Protopapas; Karim Pichara (CoRR, 2021)

Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks. - Olga Graf; Pablo Flores; Pavlos Protopapas; Karim Pichara (CoRR, 2022)

Informative regularization for a multi-layer perceptron RR Lyrae classifier under data shift. - Francisco Pérez-Galarce; Karim Pichara; Pablo Huijse; Márcio Catelán; Domingo Mery (Astron. Comput., 2023)

Distinguishing a planetary transit from false positives: a Transformer-based classification for planetary transit signals. - Helem Salinas; Karim Pichara; Rafael Brahm; Francisco Pérez-Galarce; Domingo Mery (CoRR, 2023)

Improved Uncertainty Quantification in Physics-Informed Neural Networks Using Error Bounds and Solution Bundles. - Pablo Flores; Olga Graf; Pavlos Protopapas; Karim Pichara (UAI, 2025)

Exoplanet Transit Candidate Identification in TESS Full-Frame Images via a Transformer-Based Algorithm. - Helem Salinas; Rafael Brahm; Greg Olmschenk; Richard K. Barry; Karim Pichara; Stela Ishitani Silva; Vladimir Araujo (CoRR, 2025)

A self-regulated convolutional neural network for classifying variable stars. - Francisco Pérez-Galarce; Jorge Martínez-Palomera; Karim Pichara; Pablo Huijse; Márcio Catelán (CoRR, 2025)

AI for Sustainable Future Foods. - Bianca Datta; Markus J. Buehler; Yvonne Chow; Kristina Gligoric; Dan Jurafsky; David L. Kaplan; Rodrigo Ledesma-Amaro; Giorgia Del Missier; Lisa Neidhardt; Karim Pichara; Benjamin Sanchez-Lengeling; Miek Schlangen; et al. (CoRR, 2025)