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This work presents a systematic methodology for describing the transient dynamics of coarse-grained molecular systems inferred from all-atom simulated data. We suggest Langevin-type dynamics where the coarse-grained interaction potential…

Numerical Analysis · Mathematics 2023-09-22 G. Baxevani , V. Harmandaris , E. Kalligiannaki , I. Tsantili

Discrete diffusion models (DDMs) are a powerful class of generative models for categorical data, but they typically require many function evaluations for a single sample, making inference expensive. Existing acceleration methods either rely…

Machine Learning · Computer Science 2025-12-16 Yansong Gao , Yu Sun

In this paper, a thermal-dynamical consistent model for mass transfer across permeable moving interfaces is proposed by using the energy variation method. We consider a restricted diffusion problem where the flux across the interface…

Numerical Analysis · Mathematics 2022-06-15 Yuzhe Qin , Huaxiong Huang , Yi Zhu , Chun Liu , Shixin Xu

The present article proposes a diffuse interface model for compressible multicomponent flows with transport phenomena of mass, momentum and energy (i.e., mass diffusion, viscous dissipation and heat conduction). The model is reduced from…

Analysis of PDEs · Mathematics 2022-10-26 Chao Zhang , Lifeng Wang

We analyse diffusion dynamics on weakly-coupled networks (interconnected networks) by means of separation of time scales. Using an adiabatic approximation we reduced the system dynamics to a Markov chain with aggregated variables and…

Chaotic Dynamics · Physics 2018-12-14 Grzegorz Siudem , Janusz A. Hołyst

This paper presents an analytical comparison of active and passive receiver models in diffusive molecular communication. In the active model, molecules are absorbed when they collide with the receiver surface. In the passive model, the…

Emerging Technologies · Computer Science 2017-03-20 Adam Noel , Yansha Deng , Dimitrios Makrakis , Abdelhakim Hafid

We consider a hidden Markov model, where the signal process, given by a diffusion, is only indirectly observed through some noisy measurements. The article develops a variational method for approximating the hidden states of the signal…

Optimization and Control · Mathematics 2016-10-26 Tobias Sutter , Arnab Ganguly , Heinz Koeppl

We provide a numerical study of the macroscopic model of [3] derived from an agent-based model for a system of particles interacting through a dynamical network of links. Assuming that the network remodelling process is very fast, the…

Discrete diffusion models have recently emerged as a powerful class of generative models for chemistry and biology data. In these fields, the goal is to generate various samples with high rewards (e.g., drug-likeness in molecules), making…

Machine Learning · Computer Science 2026-02-11 Prin Phunyaphibarn , Minhyuk Sung

A molecular communication channel is determined by the received signal. Received signal models form the basis for studies focused on modulation, receiver design, capacity, and coding depend on the received signal models. Therefore, it is…

Emerging Technologies · Computer Science 2016-11-21 H. Birkan Yilmaz , Changmin Lee , Yae Jee Cho , Chan-Byoung Chae

One of the main challenges in diffusion-based molecular communication is dealing with the non-linearity of reaction-diffusion chemical equations. While numerical methods can be used to solve these equations, a change in the input signals or…

Information Theory · Computer Science 2021-06-04 Hamidreza Abin , Amin Gohari , Masoumeh Nasiri-Kenari

Realistic models of the components and processes are required for molecular communication (MC) systems. In this paper, a spheroidal receiver structure is proposed for MC that is inspired by the 3D cell cultures known as spheroids being…

Emerging Technologies · Computer Science 2023-02-21 Hamidreza Arjmandi , Mohamad Zoofaghari , Mitra Rezaei , Kajsa Kanebratt , Liisa Vilen , David Janzen , Peter Gennemark , Adam Noel

Diffusion models have emerged as a promising alternative to autoregressive models in modeling discrete categorical data. However, diffusion models that directly work on discrete data space fail to fully exploit the power of iterative…

Machine Learning · Computer Science 2025-10-24 Jaehyeong Jo , Sung Ju Hwang

Dynamical systems are often subject to forcing or changes in their governing parameters and it is of interest to study how this affects their statistical properties. A prominent real-life example of this class of problems is the…

Chaotic Dynamics · Physics 2020-03-18 Manuel Santos Gutiérrez , Valerio Lucarini

Combining discrete and continuous data is an important capability for generative models. We present Discrete Flow Models (DFMs), a new flow-based model of discrete data that provides the missing link in enabling flow-based generative models…

Machine Learning · Statistics 2024-06-07 Andrew Campbell , Jason Yim , Regina Barzilay , Tom Rainforth , Tommi Jaakkola

Although diffusion models now occupy a central place in generative modeling, introductory treatments commonly assume Euclidean data and seldom clarify their connection to discrete-state analogues. This article is a self-contained primer on…

Machine Learning · Statistics 2025-12-05 Vincent Pauline , Tobias Höppe , Kirill Neklyudov , Alexander Tong , Stefan Bauer , Andrea Dittadi

Focusing on hybrid diffusion dynamics involving continuous dynamics as well as discrete events, this article investigates the explicit approximations for nonlinear switching diffusion systems modulated by a Markov chain. Different kinds of…

Numerical Analysis · Mathematics 2021-12-08 Hongfu Yang , Xiaoyue Li

In this paper, a novel time-based modulation scheme is proposed in the time-asynchronous channel for diffusion-based molecular communication systems with drift. Based on this modulation scheme, we demonstrate that the sample variance of…

Information Theory · Computer Science 2019-05-31 Qingchao Li

In diffusion-based molecular communication, information is transferred from a transmitter to a receiver using molecular carriers. The low achievable data rate is the main disadvantage of diffusion-based molecular over radio-based…

Emerging Technologies · Computer Science 2018-09-18 Tayyebeh Jahani-Nezhad , Foroogh S. Tabataba

Adaptive Markov Chain Monte Carlo (AMCMC) is a class of MCMC algorithms where the proposal distribution changes at every iteration of the chain. In this case it is important to verify that such a Markov Chain indeed has a stationary…

Probability · Mathematics 2015-09-07 Gopal K. Basak , Arunangshu Biswas
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