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Diff4Steer: Steerable Diffusion Prior for Generative Music Retrieval with Semantic Guidance
Xuchan Bao, Judith Yue Li, Zhong Yi Wan +5
Modern music retrieval systems often rely on fixed representations of user preferences, limiting their ability to capture users' diverse and uncertain retrieval needs. To address t…
A probabilistic framework for learning non-intrusive corrections to long-time climate simulations from short-time training data
Benedikt Barthel Sorensen, Leonardo Zepeda-Núñez, Ignacio Lopez-Gomez +4
Chaotic systems, such as turbulent flows, are ubiquitous in science and engineering. However, their study remains a challenge due to the large range scales, and the strong interact…
Dynamical-generative downscaling of climate model ensembles
Ignacio Lopez-Gomez, Zhong Yi Wan, Leonardo Zepeda-Núñez +3
Regional high-resolution climate projections are crucial for many applications, such as agriculture, hydrology, and natural hazard risk assessment. Dynamical downscaling, the state…
Rational-WENO: A lightweight, physically-consistent three-point weighted essentially non-oscillatory scheme
Shantanu Shahane, Sheide Chammas, Deniz A. Bezgin +8
Conventional WENO3 methods are known to be highly dissipative at lower resolutions, introducing significant errors in the pre-asymptotic regime. In this paper, we employ a rational…
DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems
Yair Schiff, Zhong Yi Wan, Jeffrey B. Parker +4
Learning dynamics from dissipative chaotic systems is notoriously difficult due to their inherent instability, as formalized by their positive Lyapunov exponents, which exponential…