SKA Science Data Challenge 2: analysis and results

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Extracting maximal information from experimental data requires access to the likelihood function, which however is never directly available for complex experiments like those performed at high energy colliders. Theoretical predictions are obtained in this ...

We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurf ...

Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models dominate in studying collective behaviour, this study introduces a deep learning model to assess social in ...

Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data st ...

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Grid cells in the entorhinal cortex (EC) encode an individual’s location in space, integrating both environmental and multisensory bodily cues. Notably, body-derived signals are also primary signals for the sense of self. While studies have demonstrated th ...

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

Accurate forecasting of photovoltaic (PV) power production is crucial for the integration of more renewable energy sources into the power grid. PV power production is highly intermittent, due to the stochastic cloud behaviour and cloud dynamics. Previous w ...

SKA Science Data Challenge 2: analysis and results

Chat with Graph Search

Boosting likelihood learning with event reweighting

Data-driven statistical optimization of a groundwater monitoring network

Predicting the long-term collective behaviour of fish pairs with deep learning

Orchestrating chromosome conformation capture analysis with Bioconductor

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Machine learning-aided generative molecular design

Changes in spatial self-consciousness elicit grid cell–like representation in the entorhinal cortex

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Network time series forecasting in photovoltaics power production