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arXiv 2025年

作者： Ao, Yunke Köhler, Johannes Prajapat, Manish As, Yarden Zeilinger, Melanie Fürnstahl, Philipp Krause, Andreas ROCS Balgrist University Hospital University of Zurich Switzerland Institute for Dynamic Systems and Control ETH Zurich Zurich Switzerland Department of Computer Science ETH Zurich Zurich Switzerland ETH AI Center ETH Zurich Zurich Switzerland

We propose a stochastic Model Predictive Control (MPC) framework that ensures closed-loop chance constraint satisfaction for linear systems with general sub-Gaussian process and measurement noise. By considering sub-Gaussian noise, we can provide guarantees for a large class of distributions, including time-varying distributions. Specifically, we first provide a new characterization of sub-Gaussian random vectors using matrix variance proxies, which can more accurately represent the predicted state distribution. We then derive tail bounds under linear propagation for the new characterization, enabling tractable computation of probabilistic reachable sets of linear systems. Lastly, we utilize these probabilistic reachable sets to formulate a stochastic MPC scheme that provides closed-loop guarantees for general sub-Gaussian noise. We further demonstrate our approach in simulations, including a challenging task of surgical planning from image *** Codes 93E20 Copyright © 2025, The Authors. All rights reserved.

关键词： Stochastic models

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LEARNING CHAOS IN A LINEAR WAY

arXiv

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arXiv 2025年

作者： Cheng, Xiaoyuan He, Yi Yang, Yiming Xue, Xiao Cheng, Sibo Giles, Daniel Tang, Xiaohang Hu, Yukun Dynamic Systems University College London United Kingdom Statistical Science University College London United Kingdom CEREA ENPC and EDF R&D Institut Polytechnique de Paris France Computer Science University College London United Kingdom

Learning long-term behaviors in chaotic dynamical systems, such as turbulent flows and climate modelling, is challenging due to their inherent instability and unpredictability. These systems exhibit positive Lyapunov exponents, which significantly hinder accurate long-term forecasting. As a result, understanding long-term statistical behavior is far more valuable than focusing on short-term accuracy. While autoregressive deep sequence models have been applied to capture long-term behavior, they often lead to exponentially increasing errors in learned dynamics. To address this, we shift the focus from simple prediction errors to preserving an invariant measure in dissipative chaotic systems. These systems have attractors, where trajectories settle, and the invariant measure is the probability distribution on attractors that remains unchanged under dynamics. Existing methods generate long trajectories of dissipative chaotic systems by aligning invariant measures, but it is not always possible to obtain invariant measures for arbitrary datasets. We propose the Poincaré Flow Neural Network (PFNN), a novel operator learning framework designed to capture behaviors of chaotic systems without any explicit knowledge of the invariant measure. PFNN employs an auto-encoder to map the chaotic system to a finite-dimensional feature space, effectively linearizing the chaotic evolution. It then learns the linear evolution operators to match the physical dynamics by addressing two critical properties in dissipative chaotic systems: (1) contraction, the system’s convergence toward its attractors, and (2) measure invariance, trajectories on the attractors following a probability distribution invariant to the dynamics. Our experiments on a variety of chaotic systems, including Lorenz systems, Kuramoto-Sivashinsky equation and Navier–Stokes equation, demonstrate that PFNN has more accurate predictions and physical statistics compared to competitive baselines including the Fourier Neural

关键词： Markov processes

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Tree Reconstruction Guarantees from CRISPR-Cas9 Lineage Tracing Data Using Neighbor-Joining 29th

Tree Reconstruction Guarantees from CRISPR-Cas9 Lineage Tra...

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29th International Conference on Research in Computational Molecular Biology, RECOMB 2025

作者： Prillo, Sebastian An, Kevin Wu, Wilson Kristanto, Ivan Jones, Matthew G. Song, Yun S. Yosef, Nir Department of Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA94720 United States Department of Systems Immunology Weizmann Institute of Science Rehovot7610001 Israel Department of Statistics University of California Berkeley BerkeleyCA94720 United States Department of Molecular and Cell Biology University of California Berkeley BerkeleyCA94720 United States Center for Personal Dynamic Regulomes Stanford University StanfordCA94305 United States

ISBN: (纸本)9783031902512

CRISPR-Cas9 based lineage tracing technologies have enabled the reconstruction of single-cell phylogenies from transcriptional readouts. However, developing tree-reconstruction algorithms with theoretical guarantees in this setting is challenging. In this work, we derive a reconstruction algorithm with theoretical guarantees using Neighbor-Joining (NJ) on distances that are moment-matched to estimate the true tree distances. We develop a series of tools to analyze this algorithm and prove its theoretical guarantees. Empirically, we show on both simulated lineage tracing data and on real data from a mouse model of lung cancer the improved performance of our method as compared to the traditional use of NJ. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

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Multi-Topic Belief Formation Through Bifurcations Over Signed Social Networks

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IEEE Transactions on Automatic Control 2025年

作者： Bizyaeva, Anastasia Franci, Alessio Leonard, Naomi E. University of Washington NSF AI Institute in Dynamic Systems Dept. of Mechanical Engineering SeattleWA98195 United States University of Liège Dept. of Electrical Engineering and Computer Science Belgium WEL Research Institute Wavre Belgium Princeton University Dept. of Mechanical and Aerospace Engineering PrincetonNJ08544 United States

We propose and analyze a nonlinear dynamic model of continuous-time multi-dimensional belief formation over signed social networks. Our model accounts for the effects of a structured belief system, self-appraisal, internal biases, and various sources of cognitive dissonance posited by recent theories in social psychology. We prove that agents become opinionated as a consequence of a bifurcation. We analyze how the balance of social network effects in the model controls the nature of the bifurcation and, therefore, the belief-forming limit-set solutions. Our analysis provides constructive conditions on how multi-stable network belief equilibria and belief oscillations emerging at a belief-forming bifurcation depend on the communication network graph and belief system network graph. Our model and analysis provide new theoretical insights on the dynamics of social systems and a new principled framework for designing decentralized decision-making on engineered networks in the presence of structured relationships among alternatives. © 1963-2012 IEEE.

关键词： Continuous time systems

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Text2Earth: Unlocking Text-driven Remote Sensing Image Generation with a Global-Scale Dataset and a Foundation Model

arXiv

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arXiv 2025年

作者： Liu, Chenyang Chen, Keyan Zhao, Rui Zou, Zhengxia Shi, Zhenwei The Department of Aerospace Intelligent Science and Technology School of Astronautics The State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China The Key Laboratory of Spacecraft Design Optimization and Dynamic Simulation Technologies Ministry of Education China Shanghai Artificial Intelligence Laboratory Shanghai200232 China Shen Yuan Honors College of Beihang University Beijing100191 China The Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

Recently, generative foundation models have significantly advanced large-scale text-driven natural image generation and have become a prominent research trend across various vertical domains. However, in the remote sensing field, there is still a lack of research on large-scale text-to-image (text2image) generation technology. Existing remote sensing image-text datasets are small in scale and confined to specific geographic areas and scene types. Besides, existing text2image methods have struggled to achieve global-scale, multi-resolution controllable, and unbounded image generation. To address these challenges, this paper presents two key contributions: the Git-10M dataset and the Text2Earth foundation model. Git-10M is a global-scale image-text dataset comprising 10.5 million image-text pairs, 5 times larger than the previous largest one. The dataset contains essential resolution information and covers a wide range of geographic scenes and contains essential geospatial metadata, significantly surpassing existing datasets in both size and diversity. Building on Git-10M, we propose Text2Earth, a 1.3 billion parameter generative foundation model based on the diffusion framework to model global-scale remote sensing scenes. Text2Earth integrates a resolution guidance mechanism, enabling users to specify image resolutions. A dynamic condition adaptation strategy is proposed for training and inference to improve image generation quality. Text2Earth not only excels in zero-shot text2image generation but also demonstrates robust generalization and flexibility across multiple tasks, including unbounded scene construction, image editing, and cross-modal image generation. This robust capability surpasses previous models restricted to the basic fixed size and limited scene types. On the previous text2image benchmark dataset, Text2Earth outperfoms previous models with a significant improvement of +26.23 FID and +20.95% Zero-shot Cls-OA metric. Our project page is https://chen-y

关键词： Optical remote sensing

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Signature of glassy dynamics in dynamic modes decompositions

arXiv

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arXiv 2025年

作者： Nicolaou, Zachary G. Cho, Hangjun Zhang, Yuanzhao Kutz, J. Nathan Brunton, Steven L. Department of Applied Mathematics University of Washington SeattleWA98195 United States Department of Mechanical Engineering University of Washington SeattleWA98195 United States AI Institute in Dynamic Systems University of Washington SeattleWA98195 United States Research Institute of Mathematics Seoul National University Seoul08826 Korea Republic of Santa Fe Institute Santa FeNM87501 United States Department of Electrical and Computer Engineering University of Washington SeattleWA98195 United States

Glasses are traditionally characterized by their rugged landscape of disordered low-energy states and their slow relaxation towards thermodynamic equilibrium. Far from equilibrium, dynamical forms of glassy behavior with anomalous algebraic relaxation have also been noted, e.g., in networks of coupled oscillators. Due to their disordered and high-dimensional nature, such systems have been difficult to study analytically, but data-driven methods are emerging as a promising alternative that may aid in their characterization. Here, we show that the gap between oscillatory and decaying modes in the Koopman spectrum vanishes in systems exhibiting algebraic relaxation. The dynamic mode decomposition, which is a data-driven spectral computation that approximates the Koopman spectrum, thus provides a model-agnostic signature for detecting and analyzing glassy dynamics. We demonstrate the utility of our approach through both a minimal example of one-dimensional ODEs and a high-dimensional example of coupled oscillators. Copyright © 2025, The Authors. All rights reserved.

关键词： Relaxation oscillators

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The university of Toronto dynamic graphics project 91

The university of Toronto dynamic graphics project

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1991 SIGCHI Conference on Human Factors in Computing systems, CHI 1991

作者： Baecker, Ronald Mantei, Marilyn Buxton, William Fiume, Eugene Dynamic Graphics Project Computer Systems Research Institute and Department of Computer Science University of Toronto Canada

No abstract available.

ISBN: (纸本)0897913833

No abstract available.

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A ccnversational extensible system for the animation of shaded images 3

A ccnversational extensible system for the animation of shad...

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3rd Annual Conference on computer Graphics and Interactive Techniques, SIGGRAPH 1976

作者： Baecker, Ronald M. Computer Systems Research Group Dynamic Graphics Project University of Torcnto TorontoON Canada

The terms "conversational" and "extensible" are defined and shown to be useful properties of computer animation systems. A conversational extensible system for the animation of shaded images is then described. With this system, implemented on a minicomputer, the animator can sketch images and movements freehand, or can define them algorithmically via the Smalltalk language. The system is itself implemented in Smalltalk, and hence can be easily extended or mcdified to suit the animator's personal style.

关键词： Animation

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Check-Mate Expert: An expert system for vibration analysis

Check-Mate Expert: An expert system for vibration analysis

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1993 Canadian Conference on Electrical and computer Engineering, CCECE 1993

作者： Lakeman, G. Gordon, K.G. Applied Research in Computer Systems Laboratory British Columbia Institute of Technology Canada Dynamic Signal Analysis Corporation Canada

This paper describes the effort by dynamic Signal Analysis Corp. and the Applied Research in Computing systems Laboratory (ARCS) to automate the vibration analysis of rotating machinery. The result of this effort is C... 详细信息

ISBN: (纸本)0780314433

关键词： Vibration analysis

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Process energy analysis and optimization in selective laser sintering

Process energy analysis and optimization in selective laser ...

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40th Annual North American Manufacturing Research Conference, NAMRC40

作者： Paul, Ratnadeep Anand, Sam Computer Aided Manufacturing Laboratory School of Dynamic Systems University of Cincinnati Cincinnati OH 45221-0072 United States

ISBN: (纸本)9781622762477

Layered Manufacturing (LM) processes are increasingly being used to manufacture complex precision parts for the automotive, aerospace and medical industries. One of the most popular LM processes is the Selective Laser Sintering (SLS) process which manufactures parts by sintering metallic, polymeric and ceramic powder under the effect of laser power. The laser energy expenditure of SLS process and its correlation to the geometry of the manufactured part and the SLS process parameters, however, have not received much attention from LM/SLS researchers. This paper presents a mathematical analysis of the laser energy required for manufacturing simple parts using the SLS process. The total energy expended is calculated as a function of the Total Area of Sintering (TAS) using a Convex Hull based approach and is correlated to the part geometry, slice thickness and the build orientation. The TAS and laser energy are calculated for three sample parts and the results are provided in the paper. Finally, an optimization model is presented which computes the minimal TAS and energy required for manufacturing a part using the SLS process.

关键词： Sintering

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