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Effective field theories of two-dimensional lattice models of fluctuating loops are constructed by mapping them onto random surfaces whose large scale fluctuations are described by a Liouville field theory. This provides a geometrical view…

Statistical Mechanics · Physics 2009-10-30 J. Kondev

We calculate the vacuum polarization functions on the lattice using the overlap fermion formulation.By matching the lattice data at large momentum scales with the perturbative expansion supplemented by Operator Product Expansion (OPE), we…

High Energy Physics - Lattice · Physics 2019-08-13 E. Shintani , S. Aoki , T. W. Chiu , S. Hashimoto , T. H. Hsieh , T. Kaneko , H. Matsufuru , J. Noaki , T. Onogi , N. Yamada

Variational inference in probabilistic graphical models aims to approximate fundamental quantities such as marginal distributions and the partition function. Popular approaches are the Bethe approximation, tree-reweighted, and other types…

Machine Learning · Statistics 2025-02-06 Harald Leisenberger , Franz Pernkopf

With the development of smart grids, High-Dimensional and Incomplete (HDI) Power Load Monitoring (PLM) data challenges the performance of Power Load Forecasting (PLF) models. In this paper, we propose a potential characterization model…

Machine Learning · Computer Science 2025-06-11 Boyu Xie , Tangtang Xie

Density functional theory (DFT)-based simulations of materials have first-principles accuracy, but are very computationally expensive. For simulating various properties of multi-component alloys, the cluster expansion (CE) technique has…

Materials Science · Physics 2026-04-01 Jacob Jeffries , Bochuan Sun , Enrique Martinez

Recent studies posit that Reinforcement Learning with Verifiable Rewards (RLVR) primarily amplifies behaviors inherent to the pre-training distribution rather than inducing new capabilities, but these insights are predominantly limited to…

Artificial Intelligence · Computer Science 2026-04-15 Minghe Shen , Zhuo Zhi , Chonghan Liu , Shuo Xing , Zhengzhong Tu , Che Liu

In this work, we introduce a novel deep learning architecture, Variable Length Embeddings (VLEs), an autoregressive model that can produce a latent representation composed of an arbitrary number of tokens. As a proof of concept, we…

Computer Vision and Pattern Recognition · Computer Science 2023-05-18 Johnathan Chiu , Andi Gu , Matt Zhou

Uncovering emergent concepts across transformer layers remains a significant challenge because the residual stream linearly mixes and duplicates information, obscuring how features evolve within large language models. Current research…

Machine Learning · Computer Science 2025-07-18 Ankur Garg , Xuemin Yu , Hassan Sajjad , Samira Ebrahimi Kahou

We calculate three-loop corrections to correlation functions of heavy-quark currents in the low- and high-energy regions. We present 30 coefficients both in the low-energy and the high-energy expansion of the scalar and the vector…

High Energy Physics - Phenomenology · Physics 2015-05-30 A. Maier , P. Marquard

Flexible Electronics (FE) technology offers uniquecharacteristics in electronic manufacturing, providing ultra-low-cost, lightweight, and environmentally-friendly alternatives totraditional rigid electronics. These characteristics enable a…

Hardware Architecture · Computer Science 2025-08-28 Polykarpos Vergos , Theofanis Vergos , Florentia Afentaki , Konstantinos Balaskas , Georgios Zervakis

Learned image compression has exhibited promising compression performance, but variable bitrates over a wide range remain a challenge. State-of-the-art variable rate methods compromise the loss of model performance and require numerous…

Image and Video Processing · Electrical Eng. & Systems 2023-03-13 Kedeng Tong , Yaojun Wu , Yue Li , Kai Zhang , Li Zhang , Xin Jin

Variational Autoencoders are widespread in Machine Learning, but are typically explained with dense math notation or static code examples. This paper presents VAE Explainer, an interactive Variational Autoencoder running in the browser to…

Human-Computer Interaction · Computer Science 2024-09-16 Donald Bertucci , Alex Endert

We develop a systematic strong coupling approach for studying an extended t-V model with interactions of a finite range. Our technique is not based on the Bethe ansatz and is applicable to both integrable and non-integrable models. We…

Strongly Correlated Electrons · Physics 2015-03-20 Marcin Szyniszewski , Evgeni Burovski

We present the Complex Envelope Variable Approximation (CEVA) as the very useful and compact method for the analysis of the essentially nonlinear dynamical systems. It allows us to study both the stationary and non-stationary dynamics even…

Pattern Formation and Solitons · Physics 2020-04-20 Valeri V. Smirnov , Leonid I. Manevitch

Optimization of applications for supercomputers of the highest performance class requires parallelization at multiple levels using different techniques. In this contribution we focus on parallelization of particle physics simulations…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-01-23 Nils Meyer , Peter Georg , Dirk Pleiter , Stefan Solbrig , Tilo Wettig

We prove a certain non-linear version of the Levi extension theorem for meromorphic functions. This means that the meromorphic function in question is supposed to be extendable along a sequence of complex curves, which are arbitrary, not…

Complex Variables · Mathematics 2015-06-04 Sergey Ivashkovich

This paper introduces a novel eXtended virtual element method, an extension of the conforming virtual element method. The XVEM is formulated by incorporating appropriate enrichment functions in the local spaces. The method is designed to…

Numerical Analysis · Mathematics 2024-06-19 Jerome Droniou , Gianmarco Manzini , Liam Yemm

In the context of the mean-field exciton-polariton (EP) theory with balanced loss and pump, we investigate the formation of lattice structures built of individual vortex-antivortex (VAV) bound states under the action of the two-dimensional…

Optics · Physics 2025-04-11 S. Sanjay , S. Saravana Veni , Boris A. Malomed

This paper devises a novel lowest-order conforming virtual element method (VEM) for planar linear elasticity with the pure displacement/traction boundary condition. The main trick is to view a generic polygon $K$ as a new one…

Numerical Analysis · Mathematics 2022-01-13 Jianguo Huang , Sen Lin , Yue Yu

In this paper we introduce learnable lattice vector quantization and demonstrate its effectiveness for learning discrete representations. Our method, termed LL-VQ-VAE, replaces the vector quantization layer in VQ-VAE with lattice-based…

Machine Learning · Computer Science 2023-10-17 Ahmed Khalil , Robert Piechocki , Raul Santos-Rodriguez