54 citations · 78 across the 9 of their papers we have counts for
9 papers
Data-Efficient Neural Operator Training via Physics-Based Active Learning
Alicja Polanska, Lorenzo Zanisi, Vignesh Gopakumar +1
Solving partial differential equations with neural operators significantly reduces computational costs but remains bottlenecked by high training data requirements. Active learning…
Learned harmonic mean estimation of the marginal likelihood for multimodal posteriors with flow matching
Alicja Polanska, Jason D. McEwen
The marginal likelihood, or Bayesian evidence, is a crucial quantity for Bayesian model comparison but its computation can be challenging for complex models, even in parameters spa…
Savage-Dickey density ratio estimation with normalizing flows for Bayesian model comparison
Kiyam Lin, Alicja Polanska, Davide Piras +2
A core motivation of science is to evaluate which scientific model best explains observed data. Bayesian model comparison provides a principled statistical approach to comparing sc…
Accelerated Bayesian parameter estimation and model selection for gravitational waves with normalizing flows
Alicja Polanska, Thibeau Wouters, Peter T. H. Pang +2
We present an accelerated pipeline, based on high-performance computing techniques and normalizing flows, for joint Bayesian parameter estimation and model selection and demonstrat…
The future of cosmological likelihood-based inference: accelerated high-dimensional parameter estimation and model comparison
Davide Piras, Alicja Polanska, Alessio Spurio Mancini +2
We advocate for a new paradigm of cosmological likelihood-based inference, leveraging recent developments in machine learning and its underlying technology, to accelerate Bayesian…
Learned harmonic mean estimation of the Bayesian evidence with normalizing flows
Alicja Polanska, Matthew A. Price, Davide Piras +2
We present the learned harmonic mean estimator with normalizing flows - a robust, scalable and flexible estimator of the Bayesian evidence for model comparison. Since the estimator…
Differentiable and accelerated wavelet transforms on the sphere and ball
Matthew A. Price, Alicja Polanska, Jessica Whitney +1
Directional wavelet dictionaries are hierarchical representations which efficiently capture and segment information across scale, location and orientation. Such representations dem…
Learned harmonic mean estimation of the marginal likelihood with normalizing flows
Alicja Polanska, Matthew A. Price, Alessio Spurio Mancini +1
Computing the marginal likelihood (also called the Bayesian model evidence) is an important task in Bayesian model selection, providing a principled quantitative way to compare mod…
Solitary states in adaptive nonlocal oscillator networks
Rico Berner, Alicja Polanska, Eckehard Schöll +1
In this article, we analyze a nonlocal ring network of adaptively coupled phase oscillators. We observe a variety of frequency-synchronized states such as phase-locked, multicluste…