Related papers: ronswanson: Building Table Models for 3ML

With the establishment of machine learning (ML) techniques in the scientific community, the construction of ML potential energy surfaces (ML-PES) has become a standard process in physics and chemistry. So far, improvements in the…

The increasing popularity of deep learning models has created new opportunities for developing AI-based recommender systems. Designing recommender systems using deep neural networks requires careful architecture design, and further…

We describe a framework to assemble permanent-magnet cubes in 3D-printed frames to construct dipole, quadrupole, and solenoid magnets, whose field, in the absence of iron, can be calculated analytically in three spatial dimensions. Rotating…

Developing complex biomolecular workflows is not always straightforward. It requires tedious developments to enable the interoperability between the different biomolecular simulation and analysis tools. Moreover, the need to execute the…

We present the simulation framework CRPropa version 3 designed for efficient development of astrophysical predictions for ultra-high energy particles. Users can assemble modules of the most relevant propagation effects in galactic and…

In this letter, we propose a novel three-dimensional conceptual model for an emerging service-oriented simulation paradigm. The model can be used as a guideline or an analytic means to find the potential and possible future directions of…

Hydrodynamical simulations are increasingly able to accurately model physical systems on stellar, galactic, and cosmological scales, however, the utility of these simulations is often limited by our ability to directly compare them with the…

AnyMOD.jl is a Julia framework for creating large-scale energy system models with multiple periods of capacity expansion. It applies a novel graphbased approach that was developed to address the challenges in modeling high levels of…

Simulation has become an essential component of designing and developing scientific experiments. The conventional procedural approach to coding simulations of complex experiments is often error-prone, hard to interpret, and inflexible,…

$clustertools$ is a Python package for analyzing star cluster simulations. The package is built around the $StarCluster$ class, which stores all data read in from the snapshot of a given model star cluster. The package contains functions…

Improvement of time series forecasting accuracy through combining multiple models is an important as well as a dynamic area of research. As a result, various forecasts combination methods have been developed in literature. However, most of…

With recent increasing computational and data requirements of scientific applications, the use of large clustered systems as well as distributed resources is inevitable. Although executing large applications in these environments brings…

This article introduces a metamodel for the Business Model Canvas (BMC) using the Unified Modelling Language (UML), together with a dedicated Domain-Specific Modelling Language (DSML) tool. Although the BMC is widely adopted by both…

This work introduces TopoBench, an open-source library designed to standardize benchmarking and accelerate research in topological deep learning (TDL). TopoBench decomposes TDL into a sequence of independent modules for data generation,…

Multiple patterning lithography has been widely adopted in advanced technology nodes of VLSI manufacturing. As a key step in the design flow, multiple patterning layout decomposition (MPLD) is critical to design closure. Due to the…

Data scientists seeking a good supervised learning model on a new dataset have many choices to make: they must preprocess the data, select features, possibly reduce the dimension, select an estimation algorithm, and choose hyperparameters…

The paper presents our system developed for table question answering (TQA). TQA tasks face challenges due to the characteristics of real-world tabular data, such as large size, incomplete column semantics, and entity ambiguity. To address…

SkyPy is an open-source Python package for simulating the astrophysical sky. It comprises a library of physical and empirical models across a range of observables and a command-line script to run end-to-end simulations. The library provides…

Simulating a survey of fluxes and redshifts (distances) from an astrophysical population is a routine task. \texttt{popsynth} provides a generic, object-oriented framework to produce synthetic surveys from various distributions and…

Astronomical software is now a fact of daily life for all hands-on members of our community. Purpose-built software for data reduction and modeling tasks becomes ever more critical as we handle larger amounts of data and simulations.…