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Related papers: An introduction to the dimer model

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We introduce an investigation about M dimers through half-filled two-site Hubbard model, that is, with two electrons. We utilize the third version of nonextensive statistical mechanics as tool for cal-culating thermodynamical and magnetic…

Statistical Mechanics · Physics 2010-02-16 F. A. R. Navarro , J. F. V. Flores

These lecture notes were prepared for a special topics course in the Department of Statistics at the University of Washington, Seattle. They comprise the first eight chapters of a book currently in progress.

Statistics Theory · Mathematics 2024-07-16 Fang Han

Contents: 1. Pomeron physics 2. Multiplicities 3. Single-particle distributions 4. Correlations and fluctuations 5. Special final states and interaction mechanisms 6. Cosmic rays and forward detectors

High Energy Physics - Phenomenology · Physics 2016-09-06 I. M. Dremin

Comment: Fisher Lecture: Dimension Reduction in Regression [arXiv:0708.3774]

Methodology · Statistics 2009-09-29 Lexin Li , Christopher J. Nachtsheim

Comment: Fisher Lecture: Dimension Reduction in Regression [arXiv:0708.3774]

Methodology · Statistics 2009-09-29 Bing Li

Comment: Fisher Lecture: Dimension Reduction in Regression [arXiv:0708.3774]

Methodology · Statistics 2007-08-30 Ronald Christensen

These notes are based on a series of six lectures, given during my stay at the CRC 701 in June/July 2008. The lecture series intended to give a survey of some of the results for the almost Mathieu operator that have been obtained since the…

Spectral Theory · Mathematics 2009-08-10 David Damanik

Distillation is the technique of training a "student" model based on examples that are labeled by a separate "teacher" model, which itself is trained on a labeled dataset. The most common explanations for why distillation "works" are…

These notes originated in a series of lectures I gave in Marseille in May, 2013. I was invited to give an introduction to the isomorphism theorems, originating with Dynkin, which connect Markov local times and Gaussian processes. This is an…

Probability · Mathematics 2014-07-08 Jay Rosen

These notes are based on lectures given at the school on Geometric and Topological Methods for Quantum Field Theory, in Villa de Leyva, Colombia, in 2009. We present a basic introduction to Dirac manifolds, recalling the original context in…

Differential Geometry · Mathematics 2011-12-22 Henrique Bursztyn

In these expository notes we draw together and develop the ideas behind some recent progress in two directions: the treatment of finite type partial differential operators by prolongation, and a class of differential complexes known as…

Differential Geometry · Mathematics 2007-05-23 A. R. Gover

This survey article on Hilbert's first and second problems is adapted from a one-hour colloquium lecture given at the University of Auckland in May, 2000, just three months before the 100th anniversary of Hilbert's lecture. It includes an…

General Mathematics · Mathematics 2007-05-23 Peter J. Nyikos

These are expanded notes of a two-semester course on Lie groups and Lie algebras given by the author at MIT.

Representation Theory · Mathematics 2026-05-26 Pavel Etingof

These are notes from the 2003 C.I.M.E. summer school "symplectic 4-manifolds and algebraic surfaces". They cover the same material as the author's (by now ancient) Ph.D. thesis.

Symplectic Geometry · Mathematics 2007-05-23 Paul Seidel

Power system cyber-physical uncertainties, including measurement ambiguities stemming from cyber attacks and data losses, along with system uncertainties introduced by massive renewables and complex dynamics, reduce the likelihood of…

Machine Learning · Computer Science 2025-02-17 Jianhua Pei , Jingyu Wang , Dongyuan Shi , Ping Wang

We explore various aspects of the correspondence between dimer models and integrable systems recently introduced by Goncharov and Kenyon. Dimer models give rise to relativistic integrable systems that match those arising from 5d N=1 gauge…

High Energy Physics - Theory · Physics 2015-05-28 Richard Eager , Sebastian Franco , Kevin Schaeffer

Diffusion models recently proved to be remarkable priors for Bayesian inverse problems. However, training these models typically requires access to large amounts of clean data, which could prove difficult in some settings. In this work, we…

Machine Learning · Computer Science 2025-11-04 François Rozet , Gérôme Andry , François Lanusse , Gilles Louppe

A brief introduction to exterior differential systems for graduate students familiar with manifolds and differential forms. For complete files, see https://github.com/Ben-McKay/introduction-to-exterior-differential-systems

Differential Geometry · Mathematics 2020-09-17 Benjamin McKay

A didactic introduction, dated by 1999, to the ideas of the papers arXiv:q-bio/0701050 and arXiv:0704.0034

Populations and Evolution · Quantitative Biology 2008-02-18 Vasily Ogryzko

Knowledge distillation is an effective approach to learn compact models (students) with the supervision of large and strong models (teachers). As empirically there exists a strong correlation between the performance of teacher and student…

Machine Learning · Computer Science 2022-10-13 Chaofei Wang , Qisen Yang , Rui Huang , Shiji Song , Gao Huang