Latent representations of transient candidates from an astronomical image difference pipeline using Variational Autoencoders. - Pablo Huijse; Nicolas Astorga; Pablo A. Estévez; Giuliano Pignata (ESANN, 2018)

Clustering of Astronomical Transient Candidates Using Deep Variational Embedding. - Nicolas Astorga; Pablo Huijse; Pablo A. Estévez; Francisco Förster (IJCNN, 2018)

Adversarial Variational Domain Adaptation. - Manuel Pérez-Carrasco; Guillermo Cabrera-Vives; Pavlos Protopapas; Nicolas Astorga; Marouan Belhaj (CoRR, 2019)

MPCC: Matching Priors and Conditionals for Clustering. - Nicolás Astorga; Pablo Huijse; Pavlos Protopapas; Pablo A. Estévez (ECCV (23), 2020)

Multi-Class Deep SVDD: Anomaly Detection Approach in Astronomy with Distinct Inlier Categories. - Manuel Pérez-Carrasco; Guillermo Cabrera-Vives; Lorena Hernández-García; Francisco Förster; Paula Sánchez-Sáez; Alejandra Muñoz Arancibia; Nicolás Astorga; Franz E. Bauer; Amelia Bayo; Martina Cádiz-Leyton; Márcio Catelán (CoRR, 2023)

Large Language Models to Enhance Bayesian Optimization. - Tennison Liu; Nicolás Astorga; Nabeel Seedat; Mihaela van der Schaar (ICLR, 2024)

Active Learning with LLMs for Partially Observed and Cost-Aware Scenarios. - Nicolás Astorga; Tennison Liu; Nabeel Seedat; Mihaela van der Schaar (NeurIPS, 2024)

Autoformulation of Mathematical Optimization Models Using LLMs. - Nicolás Astorga; Tennison Liu; Yuanzhang Xiao; Mihaela van der Schaar (CoRR, 2024)

Active Feature Acquisition for Personalised Treatment Assignment. - Julianna Piskorz; Nicolás Astorga; Jeroen Berrevoets; Mihaela van der Schaar (AISTATS, 2025)

Active Task Disambiguation with LLMs. - Kasia Kobalczyk; Nicolás Astorga; Tennison Liu; Mihaela van der Schaar (ICLR, 2025)

Continuously Updating Digital Twins using Large Language Models. - Harry Amad; Nicolás Astorga; Mihaela van der Schaar (CoRR, 2025)