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In this work, we present a generalized formulation of the Transformer algorithm by reinterpreting its core mechanisms within the framework of Path Integral formalism. In this perspective, the attention mechanism is recast as a process that…

High Energy Physics - Phenomenology · Physics 2025-05-02 Won-Gi Paeng , Daesuk Kwon , Kyungwon Jeong , Honggyo Suh

Recent feed-forward neural methods of arbitrary image style transfer mainly utilized encoded feature map upto its second-order statistics, i.e., linearly transformed the encoded feature map of a content image to have the same mean and…

Computer Vision and Pattern Recognition · Computer Science 2022-06-28 Jeong-Sik Lee , Hyun-Chul Choi

Coherent neural spiking and local field potentials are believed to be signatures of the binding and transfer of information in the brain. Coherent activity has now been measured experimentally in many regions of mammalian cortex. Synfire…

Neurons and Cognition · Quantitative Biology 2016-09-28 Zhou Wang , Andrew T Sornborger , Louis Tao

Intercellular exchange networks are essential for the adaptive capabilities of populations of cells. While diffusional exchanges have traditionally been difficult to map, recent advances in nanotechnology enable precise probing of exchange…

Statistical Mechanics · Physics 2024-12-13 Luís C. F. Latoski , Andrea De Martino , Daniele De Martino

A feed-forward neural network is demonstrated to efficiently unfold the energy distribution of protons and alpha particles passing through passive material. This model-independent approach works with unbinned data and does not require…

High Energy Physics - Experiment · Physics 2021-12-16 Ming-Liang Wong , Andrew Edmonds , Chen Wu

The celebrated Bayesian persuasion model considers strategic communication between an informed agent (the sender) and uninformed decision makers (the receivers). The current rapidly-growing literature mostly assumes a dichotomy: either the…

Computer Science and Game Theory · Computer Science 2022-03-16 Yakov Babichenko , Inbal Talgam-Cohen , Haifeng Xu , Konstantin Zabarnyi

We have previously presented the idea of how complex multimodal information could be represented in our brains in a compressed form, following mechanisms similar to those employed in machine learning tools, like autoencoders. In this short…

Neurons and Cognition · Quantitative Biology 2024-06-17 Jesus Marco de Lucas , Maria Peña Fernandez , Lara Lloret Iglesias

In this work, we describe a computational framework for the genome-wide identification and characterization of mixed transcriptional/post-transcriptional regulatory circuits in humans. We concentrated in particular on feed-forward loops…

Genomics · Quantitative Biology 2009-07-24 Angela Re , Davide Cora' , Daniela Taverna , Michele Caselle

Recent results have shown that the performance of bit-interleaved coded modulation (BICM) using convolutional codes in nonfading channels can be significantly improved when the interleaver takes a trivial form (BICM-T), i.e., when it does…

Information Theory · Computer Science 2013-03-26 Alex Alvarado , Leszek Szczecinski , Erik Agrell

Multiplex networks describe a large variety of complex systems including infrastructures, transportation networks and biological systems. Most of these networks feature a significant link overlap. It is therefore of particular importance to…

Physics and Society · Physics 2016-09-07 Davide Cellai , Sergey N. Dorogovtsev , Ginestra Bianconi

Motif scaffolding seeks to design scaffold structures for constructing proteins with functions derived from the desired motif, which is crucial for the design of vaccines and enzymes. Previous works approach the problem by inpainting or…

Biomolecules · Quantitative Biology 2024-06-06 Ke Liu , Weian Mao , Shuaike Shen , Xiaoran Jiao , Zheng Sun , Hao Chen , Chunhua Shen

Early olfactory pathway responses to the presentation of an odor exhibit remarkably similar dynamical behavior across phyla from insects to mammals, and frequently involve transitions among quiescence, collective network oscillations, and…

Neurons and Cognition · Quantitative Biology 2020-09-29 Pamela B Pyzza , Katherine A Newhall , Douglas Zhou , Gregor Kovacic , David Cai

Preceptron model updating with back propagation has become the routine of deep learning. Continuous feed forward procedure is required in order for backward propagate to function properly. Doubting the underlying physical interpretation on…

Signal Processing · Electrical Eng. & Systems 2020-10-19 Shirui Tang

Information diffusion mechanisms based on social influence models are mainly studied using likelihood of adoption when active neighbors expose a user to a message. The problem arises primarily from the fact that for the most part, this…

Social and Information Networks · Computer Science 2020-03-24 Soumajyoti Sarkar , Hamidreza Alvari , Paulo Shakarian

In physics, biology and engineering, network systems abound. How does the connectivity of a network system combine with the behavior of its individual components to determine its collective function? We approach this question for networks…

Neurons and Cognition · Quantitative Biology 2018-12-19 Yu Hu , Steven L. Brunton , Nicholas Cain , Stefan Mihalas , J. Nathan Kutz , Eric Shea-Brown

Seminal works on animal collectives started proposing a diffusive model (overdamped) for the information transfer occurring in it \cite{Vicsek}. Afterwards, the introduction of self-rotational inertia brought into play an underdamped model…

Biological Physics · Physics 2026-04-28 Mario Sandoval

The Ribosome Flow Model (RFM) describes the unidirectional movement of interacting particles along a one-dimensional chain of sites. As a site becomes fuller, the effective entry rate into this site decreases. The RFM has been used to model…

Networking and Internet Architecture · Computer Science 2015-08-26 Yoram Zarai , Oz Mendel , Michael Margaliot

The various wireless networks have made the ambient radio frequency signals around the world. Wireless information and power transfer enables the devices to recycle energy from these ambient radio frequency signals and process information…

Information Theory · Computer Science 2013-07-30 Zhiyong Chen , Biao Wang , Bin Xia , Hui Liu

We explore the bifurcation structure of a modified Cahn-Hilliard equation that describes a system that may undergo a first order phase transition and is kept permanently out of equilibrium by a lateral driving. This forms a simple model,…

Pattern Formation and Solitons · Physics 2018-07-24 Michael H. Köpf , Uwe Thiele

Classical communication paradigms focus on accurately transmitting bits over a noisy channel, and Shannon theory provides a fundamental theoretical limit on the rate of reliable communications. In this approach, bits are treated equally,…

Information Theory · Computer Science 2022-08-05 Jincheng Dai , Ping Zhang , Kai Niu , Sixian Wang , Zhongwei Si , Xiaoqi Qin