Related papers: New Directions in International Masterclasses
In an interlaboratory key comparison, a data analysis procedure for this comparison was proposed and recommended by CIPM [1, 2, 3], therein the degrees of equivalence of measurement standards of the laboratories participated in the…
Tremendous advances in laser pump-probe techniques open the door for the observation in real time of ultrafast \textit{electronic} processes. Particularly attractive is the visualization of interatomic processes where one can follow the…
Novel class discovery (NCD) aims at learning a model that transfers the common knowledge from a class-disjoint labelled dataset to another unlabelled dataset and discovers new classes (clusters) within it. Many methods, as well as elaborate…
The simultaneous detection of electromagnetic and gravitational waves from the coalescence of two neutron stars (GW170817 and GRB170817A) has ushered in a new era of "multi-messenger" astronomy, with electromagnetic detections spanning from…
Intensive Monitoring Survey of Nearby Galaxies (IMSNG) is a high cadence observation program monitoring nearby galaxies with high probabilities of hosting supernovae (SNe). IMSNG aims to constrain the SN explosion mechanism by inferring…
Quantum critical phenomena may be qualitatively different when massless Dirac fermions are present at criticality. Using our recently-discovered fermion-sign-free Majorana quantum Monte Carlo (MQMC) method introduced by us in Ref. [1], we…
In recent years, pattern analysis plays an important role in data mining and recognition, and many variants have been proposed to handle complicated scenarios. In the literature, it has been quite familiar with high dimensionality of data…
Vision foundation models can perform generalized object classification in zero-shot mode, and face/person recognition when they are fine-tuned. However, fine-tuned models suffer from catastrophic forgetting. We create models that perform…
Machine learning interatomic potentials (MLIPs) are revolutionizing the field of molecular dynamics (MD) simulations. Recent MLIPs have tended towards more complex architectures trained on larger datasets. The resulting increase in…
Breast cancer, the most common malignancy among women, requires precise detection and classification for effective treatment. Immunohistochemistry (IHC) biomarkers like HER2, ER, and PR are critical for identifying breast cancer subtypes.…
The HEIDELBERG-MOSCOW experiment, which is the most sensitive double beta decay experiment since ten years has been regularly continued until end of November 2003. An analysis of the data has been performed already until May 20, 2003. The…
Astronomy and astrophysics are regarded as highly motivating topics for students in primary and secondary schools, and they have been a recurrent and effective resource to inspire passion about science. In fact, during the last years we…
Dynamical systems are found in innumerable forms across the physical and biological sciences, yet all these systems fall naturally into universal equivalence classes: conservative or dissipative, stable or unstable, compressible or…
The International Design Study for the Neutrino Factory (the IDS-NF) was established by the community at the ninth "International Workshop on Neutrino Factories, super-beams, and beta- beams" which was held in Okayama in August 2007. The…
Multiple classifier system (MCS) has become a successful alternative for improving classification performance. However, studies have shown inconsistent results for different MCSs, and it is often difficult to predict which MCS algorithm…
We present measurements of \Omega_m and \Omega_{\Lambda} from a blind analysis of 21 high-redshift supernovae using a new technique (CMAGIC) for fitting the multi-color lightcurves of Type Ia supernovae, first introduced in Wang et al.…
In this paper, we make a comparison for the impacts of smooth dynamical dark energy, modified gravity, and interacting dark energy on the cosmological constraints on the total mass of active neutrinos. For definiteness, we consider the…
Advancements in deep learning are revolutionizing science and engineering. The immense success of deep learning is largely due to its ability to extract essential high-dimensional (HD) features from input data and make inference decisions…
Neutral current (NC) measurements play an important role in exploring new physics scenarios at long-baseline neutrino oscillation experiments. We find that combining NC measurements of the proposed Deep Underground Neutrino Experiment…
Although well-trained deep neural networks have shown remarkable performance on numerous tasks, they rapidly forget what they have learned as soon as they begin to learn with additional data with the previous data stop being provided. In…