The ever-increasing data demand craves advancements in high-speed and energy-efficient computing hardware. Analog optical neural network (ONN) processors have emerged as a promising solution, offering benefits in bandwidth and energy consumption. How...
Recent analysis of Gemini-North/NIFS H-band (1.45 - 1.8 $μ$m) observations of Uranus, recorded in 2010, with recently updated line data has revealed the spectral signature of hydrogen sulphide (H$_2$S) in Uranus's atmosphere (Irwin et al., 2018). He...
An analysis of currently available ammonia (NH$_3$) visible-to-near-infrared gas absorption data was recently undertaken by Irwin et al. (Icarus, 302 (2018) 426) to help interpret Very Large Telescope (VLT) MUSE observations of Jupiter from 0.48 - 0....
We have used sensitive archival data from the Infrared Space Observatory (ISO) to make maps of the edge-on low SFR galaxy, NGC 5907, in 6 different MIR bands: LW2, LW5, LW6, LW7, LW8, and LW10, covering the spectrum from 6.5 to 15.0 microns and inc...
In this paper, we investigate properties and limitations of invariance learned by neural networks from the data compared to the genuine invariance achieved through invariant weight-tying. To do so, we adopt a group theoretical perspective and analyze...
We propose a type-controlled framework for inquisitive question generation. We annotate an inquisitive question dataset with question types, train question type classifiers, and finetune models for type-controlled question generation. Empirical resul...
TikTok is one of the largest and fastest-growing social media sites in the world. TikTok features, however, such as voice transcripts, are often missing and other important features, such as OCR or video descriptions, do not exist. We introduce the G...
Dec 8, 2025 · Bubble Sort is the simplest sorting algorithm that works by repeatedly swapping the adjacent elements if they are in the wrong order. This algorithm is not efficient for large data sets as …
The study of flaring astrophysical events in the multi-messenger approach requires instantaneous follow-up observations to better understand the nature of these events through complementary observational data. We present Astro-COLIBRI as a platform t...
With the increased interest in computational sciences, machine learning (ML), pattern recognition (PR) and big data, governmental agencies, academia and manufacturers are overwhelmed by the constant influx of new algorithms and techniques promising i...
In the current digital age of the Internet, with ever-growing networks and data-driven business models, digital platforms and especially marketplaces are becoming increasingly important. These platforms focus primarily on digital businesses by offeri...
While traditional machine learning can effectively tackle a wide range of problems, it primarily operates within a closed-world setting, which presents limitations when dealing with streaming data. As a solution, incremental learning emerges to addre...
The increasing popularity of exercises including yoga and Pilates has created a greater demand for professional exercise video datasets in the realm of artificial intelligence. In this study, we developed 3DYoga901, which is organized within a three-...
Vision-language foundation models (VLMs), such as CLIP, exhibit remarkable performance across a wide range of tasks. However, deploying these models can be unreliable when significant distribution gaps exist between training and test data, while fine...
Esports have become major international sports with hundreds of millions of spectators. Esports games generate massive amounts of telemetry data. Using these to predict the outcome of esports matches has received considerable attention, but micro-pre...
In this paper, we demonstrate how the problem of the optimal team choice in the popular computer game Dota Underlords can be reduced to the problem of linear integer programming. We propose a model and solve it for the real data. We also prove that t...
Object detection is an important and challenging problem in computer vision. Although the past decade has witnessed major advances in object detection in natural scenes, such successes have been slow to aerial imagery, not only because of the huge va...
This paper presents a model for COVID19 in Mexico City. The data analyzed were considered from the appearance of the first case in Mexico until July 2021. In this first approximation the states considered were Susceptible, Infected, Hospitalized, Int...
Genome sequence analysis plays a pivotal role in enabling many medical and scientific advancements in personalized medicine, outbreak tracing, and forensics. However, the analysis of genome sequencing data is currently bottlenecked by the computation...
We use published OGLE LMC/SMC data to present comprehensive Period-Color (PC) and Amplitude-Color (AC) relations for both fundamental and overtone stars. For fundamental mode stars, we confirm earlier work that the minimum light extinction corrected...