Related papers: Deep Learning-Enabled Invisible Electromagnetic Sc…
In the last decades, the blossoming of experimental breakthroughs in the domain of electron energy loss spectroscopy (EELS) has triggered a variety of theoretical developments. Those have to deal with completely different situations, from…
Spectral Embedding (SE) has often been used to map data points from non-linear manifolds to linear subspaces for the purpose of classification and clustering. Despite significant advantages, the subspace structure of data in the original…
In gamma-ray astronomy and cosmic-ray physics, the continuous approximation of inverse Compton scattering (ICS) is widely adopted to model the evolution of electron energy. However, when the initial electron energy approaches $\sim100$ TeV,…
In recent years supervised representation learning has provided state of the art or close to the state of the art results in semantic analysis tasks including ranking and information retrieval. The core idea is to learn how to embed items…
The well known Lambda-system using two ground state hyperfine levels, F=1 and F=2 of 5S1/2 and one hyperfine level, F=2 of excited state of 5P3/2 of 87Rb has been recently studied using two counter- propagating control lasers [1]. The…
Integrated sensing and communication (ISAC) systems have emerged as a promising solution to improve spectrum efficiency and enable functional convergence. However, ensuring secure information transmission while maintaining high-quality…
The sixth generation (6G) communication networks are featured by integrated sensing and communications (ISAC), revolutionizing base stations (BSs) and terminals. Additionally, in the unfolding 6G landscape, a pivotal physical layer…
Sparse autoencoders (SAEs) have proven useful in disentangling the opaque activations of neural networks, primarily large language models, into sets of interpretable features. However, adapting them to domains beyond language, such as…
This paper shows that masked autoencoders (MAE) are scalable self-supervised learners for computer vision. Our MAE approach is simple: we mask random patches of the input image and reconstruct the missing pixels. It is based on two core…
Recent advancements in abilities to create and manipulate the electron's transverse wave function within the transmission electron microscope (TEM) and scanning TEM (STEM) have enabled vectorially-resolved electron energy loss (EEL) and…
This paper is concerned with the elastic near cloaking for the Lam\'e system in three-dimensions using the notion of elastic scattering coefficients (ESC). Accordingly, the ESC of arbitrary three-dimensional objects are designed and some of…
We investigate how fully-passive electromagnetic skins (EMSs) can be engineered to enhance channel charting (CC) in dense urban environments. We employ two complementary state-of-the-art CC techniques, semi-supervised t-distributed…
Over the past few decades, electroencephalography (EEG) monitoring has become a pivotal tool for diagnosing neurological disorders, particularly for detecting seizures. Epilepsy, one of the most prevalent neurological diseases worldwide,…
Deep learning models are widely used in a range of application areas, such as computer vision, computer security, etc. However, deep learning models are vulnerable to Adversarial Examples (AEs),carefully crafted samples to deceive those…
We illustrate how the future Electron-Ion Collider (EIC) can be used to discover dark bosons with masses in the $\sim$ (10~MeV -- 10~GeV) regime, having a wide range of properties. We only require that the dark bosons have a non-negligible…
Integrated Sensing and Communication (ISAC) systems enable cellular networks to jointly operate as communication technology and sense the environment. While opportunities and potential performance have been largely investigated in…
Induced Compton scattering (ICS) is a nonlinear interaction between intense electromagnetic radiation and a rarefied plasma. Although the magnetosphere of pulsars is a potential cite at which ICS occurs in nature, the ICS signatures have…
The sixth-generation (6G) mobile network is envisioned to incorporate sensing and edge artificial intelligence (AI) as two key functions. Their natural convergence leads to the emergence of Integrated Sensing and Edge AI (ISEA), a novel…
In this paper, deceptive signal-assisted private split learning is investigated. In our model, several edge devices jointly perform collaborative training, and some eavesdroppers aim to collect the model and data information from devices.…
The 2-dimensional Ising model on a square lattice is investigated with a variational autoencoder in the non-vanishing field case for the purpose of extracting the crossover region between the ferromagnetic and paramagnetic phases. The…