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Feature Learning for Bayesian Inference

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  • Projektleiter/in : Prof. Dr. Antonietta Mira
  • Co-Projektleiter/in : Prof. Dr. Fernando Perez-Cruz
  • Projektteam : Dr. Carlo Albert, Prof. Alessandro Laio, Prof. Jukka-Pekka Onnela, Dr. Simone Ulzega
  • Projektstatus : laufend
  • Drittmittelgeber : SNF
  • Kontaktperson : Simone Ulzega


The goal of this project is to use interpretable Machine Learning (ML) to find low-dimensional features in high-dimensional noisy data generated by (i) stochastic models or (ii) real systems. In both cases, the problem is to disentangle the effect of high-dimensional disturbances, such as noise or unobserved inputs, from the effects of relevant characteristics (model parameters in the first case, system properties in the latter).