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Active Feature Acquisition for Personalised Treatment Assignment
Personalised treatment via active feature acquisition.
J. Piskorz, Nicolás Astorga, J. Berrevoets, Mihaela van der Schaar
Jul 1, 2025
Auto‑formulation of Mathematical Optimisation Models Using Large Language Models
Automatically formulating optimisation models from natural language using LLMs. Accepted at ICML 2025.
Nicolás Astorga, Tennison Liu, Y. Xiao, Mihaela van der Schaar
Jun 1, 2025
arxiv
Auto‑formulation of Mathematical Optimisation Models Using Large Language Models
Continuously Updating Digital Twins Using Large Language Models
Methods for continuously updating digital twins with LLMs.
H. Amad, Nicolás Astorga, J.-M. van der Schaar
Apr 1, 2025
Active Task Disambiguation with LLMs
This paper formalizes task ambiguity and frames task disambiguation as Bayesian Experimental Design, yielding effective clarifying question selection for LLMs. Accepted at ICLR 2025.
Katarzyna Kobalczyk, Nicolás Astorga, Tennison Liu, Mihaela van der Schaar
Jan 22, 2025
arXiv
Active Task Disambiguation with LLMs
Improving LLM Generation with Inverse and Forward Alignment: Reward Modelling, Prompting, Fine‑Tuning, and Inference‑Time Optimisation
Practical techniques for improving LLM generation via inverse & forward alignment.
H. Sun, T. Pouplin, Nicolás Astorga, T. Liu, Mihaela van der Schaar
Dec 10, 2024
Active Learning with LLMs for Partially Observed and Cost‑Aware Scenarios
Active learning strategies for partially observed, cost‑aware settings via LLMs. Accepted at NeurIPS 2024.
Nicolás Astorga, Tennison Liu, N. Seedat, Mihaela van der Schaar
Dec 1, 2024
arxiv
Active Learning with LLMs for Partially Observed and Cost‑Aware Scenarios
Large Language Models to Enhance Bayesian Optimisation
Leveraging LLMs to improve Bayesian optimisation. Accepted at ICLR 2024.
Tennison Liu, Nicolás Astorga, N. Seedat, Mihaela van der Schaar
May 1, 2024
arxiv
Large Language Models to Enhance Bayesian Optimisation
MPCC: Matching Priors and Conditionals for Clustering
A GAN–VAE hybrid clustering framework leveraging forward KL.
Nicolás Astorga, P. Huijse, P. Estévez, P. Protopapas
Aug 1, 2020
Clustering of Astronomical Transient Candidates Using Deep Variational Embedding
Variational-embedding clustering for astronomical transients.
Nicolás Astorga, P. Huijse, P. A. Estévez, F. Förster
Jul 1, 2018