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In the present study, the capabilities of a new Convolutional Neural Network (CNN) model are explored with the paramount objective of reconstructing the temperature field of wall-bounded flows based on a limited set of measurement points…
We present a novel approach to transcranial ultrasound computed tomography that utilizes normalizing flows to improve the speed of imaging and provide Bayesian uncertainty quantification. Our method combines physics-informed methods and…
The redshifted 21-cm line of distant neutral H atoms provides a probe of the cosmic ``dark ages'' and the epoch of reionization (``EOR'') which ended them. The radio continuum produced by this redshifted line can be seen in absorption or…
Neutral hydrogen (HI) serves as a crucial probe for the Cosmic Dawn and the Epoch of Reionization (EoR). Actual observations of the 21-cm signal often encounter challenges such as thermal noise and various systematic effects. To overcome…
Current approximate posteriors in Bayesian neural networks (BNNs) exhibit a crucial limitation: they fail to maintain invariance under reparameterization, i.e. BNNs assign different posterior densities to different parametrizations of…
Data-driven techniques have improved the accuracy of Reynolds-averaged Navier-Stokes (RANS) models in fluid dynamics. However, modeling separated flows remains challenging due to their complex physics and sensitivity to local conditions.…
Neural Networks (NNs) have provided state-of-the-art results for many challenging machine learning tasks such as detection, regression and classification across the domains of computer vision, speech recognition and natural language…
The 21cm line from the spin-flip transition of neutral hydrogen (HI) provides a unique window into the Epoch of Reionization (EoR), the final phase transition of our Universe. The Square Kilometre Array (SKA) enables precise measurements of…
Statistical observations of the Epoch of Reionization using the 21 cm line of neutral hydrogen have the potential to revolutionize our understanding of structure formation and the first luminous objects. However, these observations are…
A possible way to study the reionization of cosmic hydrogen is by observing the large ionized regions (bubbles) around bright individual sources, e.g., quasars, using the redshifted 21 cm signal. It has already been shown that matched…
The redshifted 21-cm signal is a unique probe of the early universe, particularly the Epoch of Reionization (EoR). While the 21-cm power spectrum has been the primary statistic for parameter inference, it fails to capture the non-Gaussian…
In this note we present a fully information theoretic approach to renormalization inspired by Bayesian statistical inference, which we refer to as Bayesian Renormalization. The main insight of Bayesian Renormalization is that the Fisher…
The measurements of the 21-cm brightness temperature fluctuations from the neutral hydrogen at the Epoch of Reionization (EoR) should inaugurate the next generation of cosmological observables. In this respect, many works have concentrated…
The first generation of redshifted 21 cm detection experiments, carried out with arrays like LOFAR, MWA and GMRT, will have a very low signal-to-noise ratio per resolution element (\sim 0.2). In addition, whereas the variance of the…
Despite the recent popularity of deep generative state space models, few comparisons have been made between network architectures and the inference steps of the Bayesian filtering framework -- with most models simultaneously approximating…
We introduce the Evolution of 21-cm Structure (EOS) project: providing periodic, public releases of the latest cosmological 21-cm simulations. 21-cm interferometry is set to revolutionize studies of the Cosmic Dawn (CD) and epoch of…
Denoising diffusion models are a novel class of generative models that have recently become extremely popular in machine learning. In this paper, we describe how such ideas can also be used to sample from posterior distributions and, more…
Deep Gaussian processes (DGPs), a hierarchical composition of GP models, have successfully boosted the expressive power of their single-layer counterpart. However, it is impossible to perform exact inference in DGPs, which has motivated the…
We propose a new scheme to reconstruct the baryon acoustic oscillations (BAO) signal, which contains key cosmological information, based on deep convolutional neural networks (CNN). Trained with almost no fine-tuning, the network can…
The epoch of reionization, when photons from early galaxies ionized the intergalactic medium about a billion years after the Big Bang, is the last major phase transition in the Universe's history. Measuring the characteristics of the…