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Transformers have achieved great success in effectively processing sequential data such as text. Their architecture consisting of several attention and feedforward blocks can model relations between elements of a sequence in parallel…

Machine Learning · Computer Science 2025-02-20 Jaemu Heo , Eldor Fozilov , Hyunmin Song , Taehwan Kim

Molecular communication between biological entities is a new paradigm in communications. Recently, we studied molecular communication between two nodes formed from synthetic bacteria. Due to high randomness in behavior of bacteria, we used…

Emerging Technologies · Computer Science 2014-10-07 Arash Einolghozati , Mohsen Sardari , Faramarz Fekri

In the context of wireless communications, we propose a deep learning approach to learn the mapping from the instantaneous state of a frequency selective fading channel to the corresponding frame error probability (FEP) for an arbitrary set…

Signal Processing · Electrical Eng. & Systems 2017-11-01 Vidit Saxena , Joakim Jaldén , Mats Bengtsson , Hugo Tullberg

This paper presents a Markov-based system model for microfluidic molecular communication (MC) channels. By discretizing the advection-diffusion dynamics, the proposed model establishes a physically consistent state-space formulation. The…

Emerging Technologies · Computer Science 2025-11-11 Ruifeng Zheng , Pengjie Zhou , Pit Hofmann , Fatima Rani , Juan A. Cabrera , Frank H. P. Fitzek

A new approach for the analysis of information flow on a network is suggested using protocol parameters encapsulated in the package headers as functions of time. The minimal number of independent parameters for a complete description of the…

Chaotic Dynamics · Physics 2007-05-23 Vladimir Gudkov , Joseph E. Johnson

Channel properties influence the development of wireless communication systems. Unlike wired channels that are stationary and predictable, radio channels are extremely random and dont offer easy analysis. A Radio Propagation Model (RPM),…

Networking and Internet Architecture · Computer Science 2010-02-11 M. A. Alim , M. M. Rahman , M. M. Hossain , A. Al Nahid

A link stream is a set of triplets $(t, u, v)$ indicating that $u$ and $v$ interacted at time $t$. Link streams model numerous datasets and their proper study is crucial in many applications. In practice, raw link streams are often…

Signal Processing · Electrical Eng. & Systems 2023-11-27 Esteban Bautista , Matthieu Latapy

The Ronen method (RM) demands for successive resolutions of the diffusion equation where local diffusion constants are modified to reproduce more accurate estimates of the currents by a transport operator. The methodology is currently…

Computational Physics · Physics 2023-09-15 Johan Cufe , Daniele Tomatis , Erez Gilad

Recent advances in DNA sequencing and fluorescence imaging have made it possible to monitor the dynamics of ribosomes actively engaged in messenger RNA (mRNA) translation. Here, we model these experiments within the inhomogeneous totally…

Biological Physics · Physics 2020-07-01 Juraj Szavits-Nossan , Martin R. Evans

One limiting factor to the performance of mobile ad-hoc networks is the amount of interference that is experienced by each node. In this paper we use the Random Waypoint Mobility Model (RWPM) to represent such a network of mobile devices,…

Networking and Internet Architecture · Computer Science 2017-02-20 Pete Pratt , Carl P. Dettmann , Orestis Georgiou

Molecular Communication as the most potential methods to solve the communication in nano scale, for it's derived from nature, and it becomes more and more prevalent. Though molecular communication happens in three dimensional situation,…

Emerging Technologies · Computer Science 2016-03-14 Pengfei Lu , Zhenqiang Wu

Network flow is a powerful mathematical framework to systematically explore the relationship between structure and function in biological, social, and technological networks. We introduce a new pipelining model of flow through networks…

Neural and Evolutionary Computing · Computer Science 2019-11-04 Lavanya Marla , Lav R. Varshney , Devavrat Shah , Nirmal A. Prakash , Michael E. Gale

We introduce a method for predicting RNA folding pathways, with an application to the most important RNA tetraloops. The method is based on the idea that ensembles of three-dimensional fragments extracted from high-resolution crystal…

Biomolecules · Quantitative Biology 2016-11-21 Sandro Bottaro , Alejandro Gil-Ley , Giovanni Bussi

Numerous biological and physical processes can be modeled as systems of interacting entities evolving continuously over time, e.g. the dynamics of communicating cells or physical particles. Learning the dynamics of such systems is essential…

Radio Frequency (RF) sensing is attracting interest in research, standardization, and industry, especially for its potential in Internet of Things (IoT) applications. By leveraging the properties of the ElectroMagnetic (EM) waves used in…

Signal Processing · Electrical Eng. & Systems 2026-01-13 Federica Fieramosca , Vittorio Rampa , Michele D'Amico , Stefano Savazzi

Many theoretical works have attempted to coarse grain gene expression at the level of transcription and translation via frameworks based on exclusion processes. Usually in these models the three-dimensional conformation of the substrates…

Statistical Mechanics · Physics 2019-05-22 Lucas D. Fernandes , Luca Ciandrini

We introduce Coupled Flow Matching (CPFM), a framework that integrates controllable dimensionality reduction and high-fidelity reconstruction. CPFM learns coupled continuous flows for both the high-dimensional data x and the low-dimensional…

Machine Learning · Statistics 2025-10-28 Wenxi Cai , Yuheng Wang , Naichen Shi

In this work we present a model of an air transportation traffic system from the complex network modelling viewpoint. In the network, every node corresponds to a given airport, and two nodes are connected by means of flight routes. Each…

Physics and Society · Physics 2015-05-13 Lucas Lacasa , Miguel Cea , Massimiliano Zanin

Human motion generation is a challenging task due to its high dimensionality and the difficulty of generating fine-grained motions. Diffusion methods have been proposed due to their high sample quality and expressiveness. Early approaches…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Mirgahney Mohamed , Harry Jake Cunningham , Marc P. Deisenroth , Lourdes Agapito

Accurate RNA structure modeling remains difficult because RNA backbones are highly flexible, non-canonical interactions are prevalent, and experimentally determined 3D structures are comparatively scarce. We introduce \emph{RiboSphere}, a…

Machine Learning · Computer Science 2026-03-23 Zhou Zhang , Hanqun Cao , Cheng Tan , Fang Wu , Pheng Ann Heng , Tianfan Fu