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Unlocking Reliable Small-data AI through Bayesian Deep Learning

Objetivo

While AI for science has enabled remarkable breakthroughs in recent years, many scientists have been left underwhelmed when trying to apply AI methods in their domains. This is mainly because most scientific datasets are too small for the data-hungry modern foundation model approaches. Bayesian deep learning (BDL), combining rigorous Bayesian principles with the flexibility of neural networks, has positioned itself as a powerful remedy for this lack of data, but its adoption is hampered by some tedious design choices, most importantly, the selection of model, prior, and inference method. This proposal aims to bring the revolution of automated machine learning, which has radically boosted the adoption of conventional AI methods, into the realm of BDL. The goal is to develop an automated end-to-end pipeline that domain practitioners can autonomously use to select the best model architectures and data invariances, incorporate their own prior knowledge in an efficient and natural way, and choose the best inference method tailored to their computational resources. While many research challenges will have to be overcome to reach this ambitious goal, recent advances in BDL research, including some of my own, put me in the ideal position now to tackle these questions. Throughout this process, the research will stay grounded in real-world scientific requirements via close collaboration with domain experts in healthcare, materials science, and astrophysics. A successful completion of this project will democratize access to BDL solutions by cutting out the machine learning middlemen, thus unlocking small-data AI applications across scientific domains.

Ámbito científico (EuroSciVoc)

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Programa(s)

Tema(s)

Régimen de financiación

HORIZON-ERC - HORIZON ERC Grants

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Convocatoria de propuestas

(se abrirá en una nueva ventana) ERC-2026-STG

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Institución de acogida

TECHNISCHE UNIVERSITAT NURNBERG
Aportación neta de la UEn
€ 1 499 115,00
Dirección
Dr.-Luise-Herzberg-Straße 4
90461 NUREMBERG
Alemania
Región
Bayern Mittelfranken Nürnberg, Kreisfreie Stadt
Tipo de actividad
Higher or Secondary Education Establishments
Enlaces
Coste total
€ 1 499 115,00

Beneficiarios (1)