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Related papers: Variational Loop Vertex Expansion

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In a recent paper [Bardella et al., Entropy 26 (6), 495 (2024)] we introduced a simplified Lattice Field Theory (LFT) framework that allows experimental recordings from major Brain-Computer Interfaces (BCIs) to be interpreted in a simple…

Statistical Mechanics · Physics 2026-04-08 Simone Franchini , Giampiero Bardella

The strength and trajectory of a leading edge vortex (LEV) formed by a pitching-heaving hydrofoil (chord $c$) is studied. The LEV is identified using the $Q$-criterion method, which is calculated from the 2D velocity field obtained from PIV…

We study holomorphic extensions of one-parameter groups on locally convex spaces with a view to applications to KMS boundary conditions. In the first part we deal with analytic extensions of one-parameter groups of operators on locally…

Representation Theory · Mathematics 2023-09-19 Daniel Beltita , Karl-Hermann Neeb

In this paper we discuss extending the operating wavelength range of tunable Regenerative Amplifier FELs to shorter wavelengths than current design proposals, notably into the XUV regions of the spectrum and beyond where the reflectivity of…

Optics · Physics 2008-05-28 D. J. Dunning , B. W. J. McNeil , N. R. Thompson

The variational auto-encoder (VAE) is a deep latent variable model that has two neural networks in an autoencoder-like architecture; one of them parameterizes the model's likelihood. Fitting its parameters via maximum likelihood (ML) is…

Machine Learning · Computer Science 2021-06-03 Francisco J. R. Ruiz , Michalis K. Titsias , Taylan Cemgil , Arnaud Doucet

A variational phase space is constructed for a system of fields on Euclidean space with periodic boundary conditions. An extended action functional is defined such that the Euler-Lagrange equations generate a symplectic flow on the…

High Energy Physics - Lattice · Physics 2023-03-23 Brenden McDearmon

We present RLLTE: a long-term evolution, extremely modular, and open-source framework for reinforcement learning (RL) research and application. Beyond delivering top-notch algorithm implementations, RLLTE also serves as a toolkit for…

Artificial Intelligence · Computer Science 2024-12-06 Mingqi Yuan , Zequn Zhang , Yang Xu , Shihao Luo , Bo Li , Xin Jin , Wenjun Zeng

Cognitive modeling commonly relies on asking participants to complete a battery of varied tests in order to estimate attention, working memory, and other latent variables. In many cases, these tests result in highly variable observation…

Collective variable-based enhanced sampling methods are routinely used on systems with metastable states, where high free energy barriers impede proper sampling of the free energy landscapes when using conventional molecular dynamics…

Chemical Physics · Physics 2022-08-09 Benjamin Pampel , Omar Valsson

We develop a coarse-graining procedure for two-dimensional models of fluctuating loops by mapping them to interface models. The result is an effective field theory for the scaling limit of loop models, which is found to be a Liouville…

Condensed Matter · Physics 2015-06-25 Jane' Kondev

Although variational autoencoders (VAE) are successfully used to obtain meaningful low-dimensional representations for high-dimensional data, the characterization of critical points of the loss function for general observation models is not…

Machine Learning · Computer Science 2021-10-12 Robert Sicks , Ralf Korn , Stefanie Schwaar

Latent Video Diffusion Models (LVDMs) rely on Variational Autoencoders (VAEs) to compress videos into compact latent representations. For continuous Variational Autoencoders (VAEs), achieving higher compression rates is desirable; yet, the…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Yubo Dong , Linchao Zhu

Variational autoencoder-based voice conversion (VAE-VC) has the advantage of requiring only pairs of speeches and speaker labels for training. Unlike the majority of the research in VAE-VC which focuses on utilizing auxiliary losses or…

Sound · Computer Science 2021-12-07 Kei Akuzawa , Kotaro Onishi , Keisuke Takiguchi , Kohki Mametani , Koichiro Mori

Multivariate (MTV) porous materials exhibit unique structural complexities based on diverse spatial arrangements of multiple building block combinations. These materials possess potential synergistic functionalities that exceed the sum of…

Quantum Physics · Physics 2025-05-12 Shinyoung Kang , Younghun Kim , Jihan Kim

Quaternion-valued differential equations (QDEs) is a new kind of differential equations which have many applications in physics and life sciences. The largest difference between QDEs and ODEs is the algebraic structure. On the…

Classical Analysis and ODEs · Mathematics 2017-09-08 Kit Ian Kou , Yong-Hui Xia

Variational autoencoders (VAE) represent a popular, flexible form of deep generative model that can be stochastically fit to samples from a given random process using an information-theoretic variational bound on the true underlying…

Machine Learning · Computer Science 2019-10-08 Bin Dai , Yu Wang , John Aston , Gang Hua , David Wipf

We present lattice results on the valence-quark structure of the pion using a coordinate space method within the framework of Large Momentum Effective Theory (LaMET). In this method one relies on the matrix elements of a Euclidean…

The paper contains a development of the previously proposed generalized lattice model (GLM). In contrast to usual lattice models, the difference of the specific atomic volumes of the components is taken in account in GLM. In addition to…

Statistical Mechanics · Physics 2010-03-16 A. Yu. Zakharov , A. A. Schneider , A. L. Udovsky

In a previous paper [Nijhoff,Puttock,2003], a 2-parameter extension of the lattice potential KdV equation was derived, associated with an elliptic curve. This comprises a rather complicated 3-component system on the quad lattice which…

Exactly Solvable and Integrable Systems · Physics 2025-02-19 Frank Nijhoff , Cheng Zhang , Da-jun Zhang

We design a variational state estimation (VSE) method that provides a closed-form Gaussian posterior of an underlying complex dynamical process from (noisy) nonlinear measurements. The complex process is model-free. That is, we do not have…

Signal Processing · Electrical Eng. & Systems 2026-01-30 Gustav Norén , Anubhab Ghosh , Fredrik Cumlin , Saikat Chatterjee