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The Miniaturized Detector for Application in Space (MIDAS) is a compact device with dimensions 5 x 5 x 1 cm3 which combines position sensitive Si detectors and a fast neutrons spectrometer. MIDAS is developed with purpose to act as a linear…
In this paper, we present the results of our three-dimensional, multi-group, multi-neutrino-species radiation/hydrodynamic simulation using the state-of-the-art code F{\sc{ornax}} of the terminal dynamics of the core of a non-rotating…
We discuss the current implementation of the ALI method into our HYDrodynamical RAdiation(HYDRA) code for rapidly expanding, low density envelopes commonly found in core collapse and thermonuclear supernovae, novae and WR stars. Due to the…
Deploying Scientific Machine Learning surrogates in industrial CFD workflows requires adapting pretrained models to new vehicle families without large datasets; yet whether geometric representations learned by a geometry encoder transfer to…
A three-dimensional Monte Carlo code for modelling radiation transport in Type Ia supernovae is described. In addition to tracking Monte Carlo quanta to follow the emission, scattering and deposition of radiative energy, a scheme involving…
Neutrinos dominate the energetics of core-collapse supernovae, and are believed to play an important role in driving the explosion. The development of a spatially multidimensional neutrino radiative transfer code is a key part of the…
Sionna is a GPU-accelerated open-source library for link-level simulations based on TensorFlow. Since release v0.14 it integrates a differentiable ray tracer (RT) for the simulation of radio wave propagation. This unique feature allows for…
This paper presents a transfer learning method in speech emotion recognition based on a Time-Delay Neural Network (TDNN) architecture. A major challenge in the current speech-based emotion detection research is data scarcity. The proposed…
Physically realistic models of stellar spectra are needed in a variety of astronomical studies, from the analysis of fundamental stellar parameters, to studies of exoplanets and stellar populations in galaxies. Here we present a new version…
Particle physics simulations are the cornerstone of nuclear engineering applications. Among them radiotherapy (RT) is crucial for society, with 50% of cancer patients receiving radiation treatments. For the most precise targeting of tumors,…
One of the main diagnostic tools for measuring electron density profiles and the characteristics of long wavelength turbulent wave structures in fusion plasmas is Beam Emission Spectroscopy (BES). The increasing number of BES systems…
We study generative super-resolution (SR) in real-world scenarios where content and degradations vary across domains, genres, and segments. For example, images and videos may alternate between text overlays, fast motion, smooth cartoons,…
We describe the calculation of the stochastically heated dust emission using the 3D ray-tracing dust radiative transfer code DART-Ray, which is designed to solve the dust radiative transfer problem for galaxies with arbitrary geometries. In…
We present an updated version of SKIRT, a 3D Monte Carlo radiative transfer code developed to simulate dusty galaxies. The main novel characteristics of the SKIRT code are the use of a stellar foam to generate random positions, an efficient…
Multilinear transformations are key in high-performance computing (HPC) and artificial intelligence (AI) workloads, where data is represented as tensors. However, their high computational and memory demands, which grow with dimensionality,…
Low Earth Orbit (LEO) constellations are revolutionizing the space sector, with on-board Artificial Intelligence (AI) becoming pivotal for next-generation satellites. AI acceleration is essential for safety-critical functions such as…
The double detonation is a widely discussed explosion mechanism for Type Ia supernovae, whereby a helium shell detonation ignites a secondary detonation in the carbon/oxygen core of a white dwarf. Even for modern models that invoke…
Most 3D human mesh regressors are fully supervised with 3D pseudo-GT human model parameters and weakly supervised with GT 2D/3D joint coordinates as the 3D pseudo-GTs bring great performance gain. The 3D pseudo-GTs are obtained by…
Cloud computing allows for vast computational resources to be leveraged quickly and easily in bursts as and when required. Using the Amazon Elastic Compute Cloud and the Amazon Simple Storage Solution, we describe a technique that allows…
Transformer-based autoregressive models offer an efficient alternative to diffusion- and flow-matching-based approaches for generating 3D molecules. One challenge remains: standard transformer architectures require a sequential ordering of…