Related papers: New Directions in International Masterclasses
Recent advances in machine learning, coupled with low-cost computation, availability of cheap streaming sensors, data storage and cloud technologies, has led to widespread multi-disciplinary research activity with significant interest and…
Leptonic \textit{CP} violation search, neutrino mass hierarchy determination, and the precision measurement of oscillation parameters for a unitary test of the leptonic mixing matrix are among the major targets of the ongoing and future…
Learning from imperfect data becomes an issue in many industrial applications after the research community has made profound progress in supervised learning from perfectly annotated datasets. The purpose of the Learning from Imperfect Data…
The ILC physics working group is a mixture of experimentalists and theorists mainly working in Japan. It has its origin in the previous LC physics study group and has been reformed with the initiative of a JSPS Creative Scientific Research…
Deployment of modern TinyML tasks on small battery-constrained IoT devices requires high computational energy efficiency. Analog In-Memory Computing (IMC) using non-volatile memory (NVM) promises major efficiency improvements in deep neural…
We summarize the objectives and results of the ``international scoping study of a future neutrino factory and superbeam facility'' (ISS) physics working group. Furthermore, we discuss how the ISS study should develop into a neutrino factory…
In-Context Learning (ICL) is an emergent capability of Large Language Models (LLMs). Only a few demonstrations enable LLMs to be used as blackbox for new tasks. Previous studies have shown that using LLMs' outputs as labels is effective in…
The upcoming 4-m International Liquid Mirror Telescope (ILMT) facility will perform deep imaging (in single scan $g'$ $\sim$22 mag.) of a narrow strip of sky each clear night in the Time Delayed Integration mode. A cadence of one day…
Measuring neutrino mass ordering (NMO) poses a fundamental challenge in neutrino physics. To address this, the Jiangmen Underground Neutrino Observatory (JUNO) experiment is scheduled to commence data collection in late 2024, with the…
We demonstrate a new type of analysis for the DRIFT-IId directional dark matter detector using a machine learning algorithm called a Random Forest Classifier. The analysis labels events as signal or background based on a series of selection…
Kilometer scale neutrino telescopes are now being constructed (IceCube) and designed (KM3NeT). While no neutrino flux of cosmic origin has been discovered so far, the first weak signals are expected to be discerned in the next few years.…
The IceCube Neutrino Observatory has observed a sample of high purity, primarily atmospheric, muon neutrino events over 11 years from all directions below the horizon, spanning the energy range 500 GeV to 100 TeV. While this sample was…
Linear discriminant analysis (LDA) is a popular technique to learn the most discriminative features for multi-class classification. A vast majority of existing LDA algorithms are prone to be dominated by the class with very large deviation…
The International Linear Collider (ILC) will advance our understanding of fundamental physics, through a program for precision measurements of the Higgs boson and of the top quark properties. An additional crucial goal of the ILC will be…
Intra-class variability is given according to the significance in the degree of dissimilarity between images within a class. In that sense, depending on its intensity, intra-class variability can hinder the learning process for DL models,…
Visual food recognition in real-world dietary logging scenarios naturally exhibits severe data imbalance, where a small number of food categories appear frequently while many others occur rarely, resulting in long-tailed class…
We report on an initiative that seeks to encourage high school girls to develop critical thinking and transferable skills widely used in scientific work, as well as to generate a concrete space of opportunities for girls to experience how…
The Mu2e experiment at Fermilab is being designed to study the coherent neutrino-less conversion of a negative muon into an electron in the field of a nucleus. This process has an extremely low probability in the Standard Model and its…
The ordering of the neutrino mass eigenstates is one of the fundamental open questions in neutrino physics. While current-generation neutrino oscillation experiments are able to produce moderate indications on this ordering, upcoming…
Machine learning (ML) is revolutionizing the world, affecting almost every field of science and industry. Recent algorithms (in particular, deep networks) are increasingly data-hungry, requiring large datasets for training. Thus, the…