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Invertible flow-based generative models are an effective method for learning to generate samples, while allowing for tractable likelihood computation and inference. However, the invertibility requirement restricts models to have the same…

Machine Learning · Computer Science 2020-02-21 Abhishek Kumar , Ben Poole , Kevin Murphy

We present a novel diffusion-based framework for synthesizing 2D vector fields from sparse, coherent inputs (i.e., streamlines) while maintaining physical plausibility. Our method employs a conditional denoising diffusion probabilistic…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Nguyen K. Phan , Ricardo Morales , Sebastian D. Espriella , Guoning Chen

Data assimilation plays a crucial role in numerical modeling, enabling the integration of real-world observations into mathematical models to enhance the accuracy and predictive capabilities of simulations. This approach is widely applied…

Numerical Analysis · Mathematics 2024-11-08 Alexander Lobbe , Dan Crisan , Oana Lang

Diffusion models have recently driven significant breakthroughs in generative modeling. While state-of-the-art models produce high-quality samples on average, individual samples can still be low quality. Detecting such samples without human…

Machine Learning · Computer Science 2025-06-13 Metod Jazbec , Eliot Wong-Toi , Guoxuan Xia , Dan Zhang , Eric Nalisnick , Stephan Mandt

Flow matching has recently emerged as a promising alternative to diffusion-based generative models, offering faster sampling and simpler training by learning continuous flows governed by ordinary differential equations. Despite growing…

Machine Learning · Computer Science 2025-12-02 Mudit Gaur , Prashant Trivedi , Shuchin Aeron , Amrit Singh Bedi , George K. Atia , Vaneet Aggarwal

Bayesian Flow Networks (BFNs) has been recently proposed as one of the most promising direction to universal generative modelling, having ability to learn any of the data type. Their power comes from the expressiveness of neural networks…

Machine Learning · Computer Science 2023-10-19 Mateusz Pyla , Kamil Deja , Bartłomiej Twardowski , Tomasz Trzciński

We investigate D=4, N=1 F theory models realized by type IIB string compactification on toric threefolds. Massless spectra, gauge symmetries, phase transitions associated with divisor contractions and flops, and non-perturbative…

High Energy Physics - Theory · Physics 2009-10-30 Kenji Mohri

A generative modeling framework is proposed that combines diffusion models and manifold learning to efficiently sample data densities on manifolds. The approach utilizes Diffusion Maps to uncover possible low-dimensional underlying (latent)…

Machine Learning · Computer Science 2025-04-22 Dimitris G. Giovanis , Ellis Crabtree , Roger G. Ghanem , Ioannis G. Kevrekidis

Speculative sampling is a popular technique for accelerating inference in Large Language Models by generating candidate tokens using a fast draft model and accepting or rejecting them based on the target model's distribution. While…

Machine Learning · Computer Science 2025-07-08 Valentin De Bortoli , Alexandre Galashov , Arthur Gretton , Arnaud Doucet

We discuss a number of issues arising when computing non-perturbative effects systematically across the string theory landscape. In particular, we cast the study of fairly generic physical properties into the language of…

High Energy Physics - Theory · Physics 2015-05-20 Mirjam Cvetič , Iñaki García-Etxebarria , James Halverson

Generative flows models enjoy the properties of tractable exact likelihood and efficient sampling, which are composed of a sequence of invertible functions. In this paper, we incorporate matrix exponential into generative flows. Matrix…

Machine Learning · Computer Science 2020-07-21 Changyi Xiao , Ligang Liu

We study the vacuum structure of compactifications of type II string theories on orientifolds with SU(3)xSU(3) structure. We argue that generalised geometry enables us to treat these non-geometric compactifications using a supergravity…

High Energy Physics - Theory · Physics 2010-10-27 Andrei Micu , Eran Palti , Gianmassimo Tasinato

We consider, in a string theory framework, physical processes of phenomenological interest in models with a low string scale. The amplitudes we study involve tree-level virtual gravitational exchange, divergent in a field-theoretical…

High Energy Physics - Theory · Physics 2011-07-19 E. Dudas , J. Mourad

In this paper we present a large class of flux backgrounds and solve the shortest vector problem in type IIB string theory on an orientifold of the $1^9$ Landau-Ginzburg model.

High Energy Physics - Theory · Physics 2023-11-16 Katrin Becker , Nathan Brady , Anindya Sengupta

We investigate a simple extra-dimensional model and its four-dimensional vacua. This model has a two-form flux and a positive cosmological constant, and the extra dimensions are compactified as the product of $N$ two-spheres. The theory is…

High Energy Physics - Theory · Physics 2014-08-20 Adam R. Brown , Alex Dahlen , Ali Masoumi

This article is the PhD thesis of the author. It is focused on Type II compactifications because of the potential for the construction of realistic MSSM-like compactifications. In particular we concentrate in Type IIB Calabi-Yau…

High Energy Physics - Theory · Physics 2012-10-02 Luis Aparicio

These lecture notes provide a pedagogical introduction, with exercises, to the techniques used in attempts to construct vacua with stabilised moduli in string theory. The reader is only assumed to have a basic knowledge of general…

High Energy Physics - Theory · Physics 2023-05-15 Thomas Van Riet , Gianluca Zoccarato

The properties of the effective scalar potential are studied in the framework of type IIB string theory, taking into account perturbative and non-perturbative corrections. The former modify the K\"ahler potential and include $\alpha'$ and…

High Energy Physics - Theory · Physics 2020-10-07 Vasileios Basiouris , George K. Leontaris

We derive formulas for counting certain classes of vacua in the string/M theory landscape. We do so in the context of the moduli space of M-theory compactifications on singular manifolds with G_2 holonomy. Particularly, we count the numbers…

High Energy Physics - Theory · Physics 2015-06-12 Tamar Friedmann , Richard P. Stanley

The search for classically stable Type IIA de-Sitter vacua typically starts with an ansatz that gives Anti-de-Sitter supersymmetric vacua and then raises the cosmological constant by modifying the compactification. As one raises the…

High Energy Physics - Theory · Physics 2015-06-03 Xingang Chen , Gary Shiu , Yoske Sumitomo , S. -H. Henry Tye
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