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As machine learning-enabled Text-to-Image (TTI) systems are becoming increasingly prevalent and seeing growing adoption as commercial services, characterizing the social biases they exhibit is a necessary first step to lowering their risk…

Computers and Society · Computer Science 2023-11-13 Alexandra Sasha Luccioni , Christopher Akiki , Margaret Mitchell , Yacine Jernite

The well-known Ising model used in statistical physics was adapted to a social dynamics context to simulate the adoption of a technological innovation. The model explicitly combines (a) an individual's perception of the advantages of an…

Physics and Society · Physics 2015-05-20 Carlos E. Laciana , Santiago L. Rovere

Generative foundation models like Stable Diffusion comprise a diverse spectrum of knowledge in computer vision with the potential for transfer learning, e.g., via generating data to train student models for downstream tasks. This could…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Leonhard Hennicke , Christian Medeiros Adriano , Holger Giese , Jan Mathias Koehler , Lukas Schott

The diffusion equation is the primary tool to study the movement dynamics of a free Brownian particle, but when spatial heterogeneities in the form of permeable interfaces are present, no fundamental equation has been derived. Here we…

Statistical Mechanics · Physics 2022-09-14 Toby Kay , Luca Giuggioli

We analyze purely competitive many-species Lotka-Volterra systems with random interaction matrices, focusing the attention on statistical properties of their asymptotic states. Generic features of the evolution are outlined from a…

adap-org · Physics 2009-10-30 Guillermo Abramson , Damian Zanette

In real-life conversations, the content is diverse, and there exists the one-to-many problem that requires diverse generation. Previous studies attempted to introduce discrete or Gaussian-based continuous latent variables to address the…

Computation and Language · Computer Science 2024-04-11 Jianxiang Xiang , Zhenhua Liu , Haodong Liu , Yin Bai , Jia Cheng , Wenliang Chen

Diffusion models offer stable training and state-of-the-art performance for deep generative modeling tasks. Here, we consider their use in the context of multivariate subsurface modeling and probabilistic inversion. We first demonstrate…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Roberto Miele , Niklas Linde

Lie group methods are applied to the time-dependent, monoenergetic neutron diffusion equation in materials with spatial and time dependence. To accomplish this objective, the underlying 2nd order partial differential equation (PDE) is…

Analysis of PDEs · Mathematics 2019-03-21 Jesse F. Giron , Scott D. Ramsey , Brian A. Temple

The dynamics of a local community of competing species with weak immigration from a static regional pool is studied. Implementing the generalized competitive Lotka-Volterra model with demographic noise, a rich dynamics structure with four…

Populations and Evolution · Quantitative Biology 2015-06-22 David A. Kessler , Nadav M. Shnerb

The versatility of renewal theory is owed to its abstract formulation. Renewals can be interpreted as steps of a random walk, switching events in two-state models, domain crossings of a random motion, etc. We here discuss a renewal process…

Statistical Mechanics · Physics 2014-03-03 Johannes H. P. Schulz , Eli Barkai , Ralf Metzler

In this article we focus on evolving information systems. First a delimitation of the concept of evolution is provided, resulting in a first attempt to a general theory for such evolutions. The theory makes a distinction between the…

Artificial Intelligence · Computer Science 2021-05-25 H. A. Proper , Th. P. van der Weide

Conditional diffusion models serve as the foundation of modern image synthesis and find extensive application in fields like computational biology and reinforcement learning. In these applications, conditional diffusion models incorporate…

Machine Learning · Computer Science 2024-03-19 Hengyu Fu , Zhuoran Yang , Mengdi Wang , Minshuo Chen

Diffusion models (DMs) represent state-of-the-art generative models for continuous inputs. DMs work by constructing a Stochastic Differential Equation (SDE) in the input space (ie, position space), and using a neural network to reverse it.…

Machine Learning · Computer Science 2024-05-14 Tianrong Chen , Jiatao Gu , Laurent Dinh , Evangelos A. Theodorou , Joshua Susskind , Shuangfei Zhai

Volume-filling cross-diffusion equations for the components of a tissue structure are formally derived from mass conservation laws and force balances for the interphase pressures and viscous drag forces in a multiphase approach. The…

Analysis of PDEs · Mathematics 2026-04-03 Ansgar Jüngel , Cordula Reisch , Sara Xhahysa

In this paper we describe a novel framework for diffusion-based generative modeling on constrained spaces. In particular, we introduce manual bridges, a framework that expands the kinds of constraints that can be practically used to form…

Machine Learning · Computer Science 2025-02-28 Saeid Naderiparizi , Xiaoxuan Liang , Berend Zwartsenberg , Frank Wood

Horizontal transfer (HT) of heritable information or `traits' (carried by genetic elements, endosymbionts, or culture) is widespread among living organisms. Yet current ecological and evolutionary theory addressing HT is limited. We present…

Populations and Evolution · Quantitative Biology 2015-12-01 Sylvain Billiard , Pierre Collet , Régis Ferrière , Sylvie Méléard , Viet Chi Tran

In complex ecological communities, species may self-organize into clusters or clumps where highly similar species can coexist. The emergence of such species clusters can be captured by the interplay between neutral and niche theories. Based…

Statistical Mechanics · Physics 2026-04-16 Shing Yan Li , Mehran Kardar , Zhijie Feng , Washington Taylor

Diffusion Models have become a cornerstone of modern generative AI for their exceptional generation quality and controllability. However, their inherent \textit{multi-step iterations} and \textit{complex backbone networks} lead to…

Although definitions of technology exist to explain the patterns of technological innovations, there is no general definition that explain the role of technology for humans and other animal species in environment. The goal of this study is…

General Economics · Economics 2019-09-13 Mario Coccia

Remote sensing change detection is often challenged by spatial misalignment between bi-temporal images, especially when acquisitions are separated by long seasonal or multi-year gaps. While modern convolutional and transformer-based models…

Computer Vision and Pattern Recognition · Computer Science 2025-11-12 Seyedehanita Madani , Vishal M. Patel
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