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Separating high-dimensional data like images into independent latent factors, i.e independent component analysis (ICA), remains an open research problem. As we show, existing probabilistic deep generative models (DGMs), which are…

Machine Learning · Computer Science 2021-02-01 Alexander Camuto , Matthew Willetts , Brooks Paige , Chris Holmes , Stephen Roberts

We consider an SO(10) GUT model from F-theory compactified on an elliptically fibered Calabi-Yau with a D5 singularity. To obtain the matter curves and the Yukawa couplings, we use a global description to resolve the singularity. We…

High Energy Physics - Theory · Physics 2015-06-05 Radu Tatar , William Walters

We investigate a principled approach for symbolic operation completion (SOC), a minimal task for studying symbolic reasoning. While conceptually similar to matrix completion, SOC poses a unique challenge in modeling abstract relationships…

Machine Learning · Computer Science 2024-05-24 Dongsung Huh

We consider four dimensional heterotic compactifications on smooth elliptic Calabi-Yau threefolds. Using spectral cover techniques, we study bundle cohomology groups corresponding to charged matter multiplets. The analysis shows that in…

High Energy Physics - Theory · Physics 2010-02-03 Duiliu-Emanuel Diaconescu , Gheorghe Ionesei

A review of orbifold geometry is given, followed by a review of the construction of four-dimensional heterotic string models by compactification on a six-dimensional Z_3 orbifold. Particular attention is given to the details of the…

High Energy Physics - Phenomenology · Physics 2007-05-23 Joel Giedt

We introduce a novel method to teach a robotic agent to interactively explore cluttered yet structured scenes, such as kitchen pantries and grocery shelves, by leveraging the physical plausibility of the scene. We propose a novel learning…

Robotics · Computer Science 2021-09-23 K. Niranjan Kumar , Irfan Essa , Sehoon Ha

Model-based compression is an effective, facilitating, and expanded model of neural network models with limited computing and low power. However, conventional models of compression techniques utilize crafted features [2,3,12] and explore…

Machine Learning · Statistics 2018-07-10 Hamed Hakkak

Reasoning about the future behavior of other agents is critical to safe robot navigation. The multiplicity of plausible futures is further amplified by the uncertainty inherent to agent state estimation from data, including positions,…

Computer Vision and Pattern Recognition · Computer Science 2022-03-04 Boris Ivanovic , Kuan-Hui Lee , Pavel Tokmakov , Blake Wulfe , Rowan McAllister , Adrien Gaidon , Marco Pavone

Employing graph neural networks (GNNs) for graph clustering has shown promising results in deep graph clustering. However, existing methods disregard the reciprocal relationship between representation learning and structure augmentation:…

Machine Learning · Computer Science 2026-05-19 Shifei Ding , Benyu Wu , Xiao Xu , Ling Ding , Xindong Wu

We study a distributed learning problem in which learning agents are embedded in a directed acyclic graph (DAG). There is a fixed and arbitrary distribution over feature/label pairs, and each agent or vertex in the graph is able to directly…

Machine Learning · Computer Science 2025-10-13 Michael Kearns , Aaron Roth , Emily Ryu

With the advent of future big-data surveys, automated tools for unsupervised discovery are becoming ever more necessary. In this work, we explore the ability of deep generative networks for detecting outliers in astronomical imaging…

Deep reinforcement learning has been applied successfully to solve various real-world problems and the number of its applications in the multi-agent settings has been increasing. Multi-agent learning distinctly poses significant challenges…

Machine Learning · Computer Science 2021-02-24 Ngoc Duy Nguyen , Thanh Thi Nguyen , Doug Creighton , Saeid Nahavandi

We present an inductive algebraic approach to the systematic construction and classification of generalized Calabi-Yau (CY) manifolds in different numbers of complex dimensions, based on Batyrev's formulation of CY manifolds as toric…

High Energy Physics - Theory · Physics 2009-09-11 F. Anselmo , J. Ellis , D. V. Nanopoulos , G. Volkov

Machine learning provides a novel avenue for the study of experimental realizations of many-body systems, and has recently been proven successful in analyzing properties of experimental data of ultracold quantum gases. We here show that…

Computational Physics · Physics 2021-09-29 Corneel Casert , Kyle Mills , Tom Vieijra , Jan Ryckebusch , Isaac Tamblyn

We construct, as hypersurfaces in toric varieties, Calabi-Yau manifolds corresponding to F-theory vacua dual to E8*E8 heterotic strings compactified to six dimensions on K3 surfaces with non-semisimple gauge backgrounds. These vacua were…

High Energy Physics - Theory · Physics 2009-10-30 Philip Candelas , Eugene Perevalov , Govindan Rajesh

We introduce manifold-learning flows (M-flows), a new class of generative models that simultaneously learn the data manifold as well as a tractable probability density on that manifold. Combining aspects of normalizing flows, GANs,…

Machine Learning · Statistics 2020-11-16 Johann Brehmer , Kyle Cranmer

We examine compactifications of heterotic string theory on manifolds with SU(3) structure. In particular, we study N = 1/2 domain wall solutions which correspond to the perturbative vacua of the 4D, N =1 supersymmetric theories associated…

High Energy Physics - Theory · Physics 2015-06-05 James Gray , Magdalena Larfors , Dieter Lust

We give a complete list of a class of three-generation models in E8 x E8 heterotic string theory and its dual F-theory on an elliptic Calabi-Yau over a (generalized) Hirzebruch variety in which the divisors of the relevant line bundles…

High Energy Physics - Theory · Physics 2016-07-12 Shun'ya Mizoguchi , Tomoki Sakaguchi

We calculate, at the classical level, the superpotential tri-linear couplings of the only known globally consistent heterotic minimal supersymmetric Standard Model [ hep-th/0512149 ]. This recently constructed model is based on a…

High Energy Physics - Theory · Physics 2008-11-26 Vincent Bouchard , Mirjam Cvetic , Ron Donagi

Grand unification groups (GUTs) are constructed from SO(32) heterotic string via $\Z_{12-I}$ orbifold compactification. So far, most phenomenological studies from string compactification relied on $\EE8$ heterotic string, and this invites…

High Energy Physics - Theory · Physics 2020-11-13 Jihn E. Kim
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