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We study the diffusion of information in an overlaying social-physical network. Specifically, we consider the following set-up: There is a physical information network where information spreads amongst people through conventional…

Social and Information Networks · Computer Science 2013-09-03 Osman Yagan , Dajun Qian , Junshan Zhang , Douglas Cochran

Encoding and decoding models are widely used in systems, cognitive, and computational neuroscience to make sense of brain-activity data. However, the interpretation of their results requires care. Decoding models can help reveal whether…

Neurons and Cognition · Quantitative Biology 2019-04-29 Nikolaus Kriegeskorte , Pamela K. Douglas

This paper provides a perspective on applying the concepts of information thermodynamics, developed recently in non-equilibrium statistical physics, to problems in theoretical neuroscience. Historically, information and energy in…

Neurons and Cognition · Quantitative Biology 2024-09-27 Jan Karbowski

Living organisms rely on molecular networks, such as gene circuits and signaling pathways, for information processing and robust decision-making in crowded, noisy environments. Recent advances show that interacting biomolecules…

Life depends as much on the flow of information as on the flow of energy. Here we review the many efforts to make this intuition precise. Starting with the building blocks of information theory, we explore examples where it has been…

Quantitative Methods · Quantitative Biology 2014-12-31 Gašper Tkačik , William Bialek

Spreading information through a network of devices is a core activity for most distributed systems. As such, self-stabilizing algorithms implementing information spreading are one of the key building blocks enabling aggregate computing to…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-02-23 Yuanqiu Mo , Soura Dasgupta , Jacob Beal

The propagation of elastic waves in soft materials plays a crucial role in the spatio-temporal transmission of mechanical signals, e.g. in biological mechanotransduction or in the failure of marginal solids. At high Reynolds numbers $Re \gg…

Microscopic biological systems operate far from equilibrium, are subject to strong fluctuations, and are composed of many coupled components with interactions varying in nature and strength. Researchers are actively investigating the…

Statistical Mechanics · Physics 2023-12-25 Emma Lathouwers , David A. Sivak

We present a new framework for analyzing the evolution of information in geophysical systems. Understanding how information, and its counterpart, uncertainty, propagates is central to predictability studies and has significant implications…

Information Theory · Computer Science 2026-01-06 Peter Jan van Leeuwen

This paper reviews machine learning applications and approaches to detection, classification and control of intelligent materials and structures with embedded distributed computation elements. The purpose of this survey is to identify…

Machine Learning · Computer Science 2016-06-14 Dana Hughes , Nikolaus Correll

The mechanisms of information transmission are investigated in a lattice of coupled continuous maps, by analyzing the propagation of both finite and infinitesimal disturbances. Two distinct regimes are detected: in the former case, both…

chao-dyn · Physics 2009-10-22 Antonio Politi , Alessandro Torcini

Biological organisms adapt to changes by processing informations from different sources, most notably from their ancestors and from their environment. We review an approach to quantify these informations by analyzing mathematical models of…

Populations and Evolution · Quantitative Biology 2016-03-23 Olivier Rivoire

Effective information analysis generally boils down to properly identifying the structure or geometry of the data, which is often represented by a graph. In some applications, this structure may be partly determined by design constraints or…

Machine Learning · Computer Science 2016-11-07 Dorina Thanou , Xiaowen Dong , Daniel Kressner , Pascal Frossard

It is shown that information transmission inside a cell can occur by means of mechanical waves transmitted through DNA. The propagation of the waves is strongly dependent on the shape of the DNA thus proteins that change the shape of DNA…

Biological Physics · Physics 2007-05-23 Thomas C. Bishop , Oleksandr O. Zhmudsky

Wave propagation on the surface of a material contains information about physical properties beneath its surface. We propose a method for inferring the thickness and stiffness of a structure from just a video of waves on its surface. Our…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Alexander C. Ogren , Berthy T. Feng , Jihoon Ahn , Katherine L. Bouman , Chiara Daraio

Knowledge graphs enable data scientists to learn end-to-end on heterogeneous knowledge. However, most end-to-end models solely learn from the relational information encoded in graphs' structure: raw values, encoded as literal nodes, are…

Machine Learning · Computer Science 2023-09-06 W. X. Wilcke , P. Bloem , V. de Boer , R. H. van t Veer

We study the heat transfer between elastic solids with randomly rough surfaces. We include both the heat transfer from the area of real contact, and the heat transfer between the surfaces in the noncontact regions. We apply a recently…

Soft Condensed Matter · Physics 2009-08-28 B. N. J. Persson , B. Lorenz , A. I. Volokitin

Steganography, the art of information hiding, has continually evolved across visual, auditory and linguistic domains, adapting to the ceaseless interplay between steganographic concealment and steganalytic revelation. This study seeks to…

Robotics · Computer Science 2025-01-09 Ching-Chun Chang , Yijie Lin , Isao Echizen

Information, ideas, and diseases, or more generally, contagions, spread over space and time through individual transmissions via social networks, as well as through external sources. A detailed picture of any diffusion process can be…

Social and Information Networks · Computer Science 2021-02-08 Fangcao Xu , Bruce Desmarais , Donna Peuquet

Embeddings are functions that map raw input data to low-dimensional vector representations, while preserving important semantic information about the inputs. Pre-training embeddings on a large amount of unlabeled data and fine-tuning them…

Machine Learning · Computer Science 2020-08-21 Congzheng Song , Ananth Raghunathan