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Diffusion models have fundamentally transformed the field of generative models, making the assessment of similarity between customized model outputs and reference inputs critically important. However, traditional perceptual similarity…

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Neural sequence models are widely used to model time-series data. Equally ubiquitous is the usage of beam search (BS) as an approximate inference algorithm to decode output sequences from these models. BS explores the search space in a…

Artificial Intelligence · Computer Science 2018-10-23 Ashwin K Vijayakumar , Michael Cogswell , Ramprasath R. Selvaraju , Qing Sun , Stefan Lee , David Crandall , Dhruv Batra

With the aim of generalizing histogram statistics to higher dimensional cases, density estimation via discrepancy based sequential partition (DSP) has been proposed to learn an adaptive piecewise constant approximation defined on a binary…

Machine Learning · Statistics 2025-12-23 Zhengyang Lei , Lirong Qu , Sihong Shao , Yunfeng Xiong

We propose an efficient method for searching for color vibration pairs that are imperceptible to the human eye based on the MacAdam ellipse, an experimentally determined color-difference range that is indistinguishable to the human eye. We…

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Cosmological analyses of samples of photometrically-identified Type Ia supernovae (SNe Ia) depend on understanding the effects of 'contamination' from core-collapse and peculiar SN Ia events. We employ a rigorous analysis on…

This letter presents a high-dimensional analysis of the training dynamics for a single-layer nonlinear contrastive learning model. The empirical distribution of the model weights converges to a deterministic measure governed by a…

Machine Learning · Computer Science 2024-06-12 Lineghuan Meng , Chuang Wang

We study optical light curve(LC) relations of type Ia supernovae(SNe~Ia) for their use in cosmology using high-quality photometry published by the Carnegie-Supernovae-Project (CSP-I). We revisit the classical luminosity-decline-rate…

Neural Ordinary Differential Equations (NODEs), a framework of continuous-depth neural networks, have been widely applied, showing exceptional efficacy in coping with representative datasets. Recently, an augmented framework has been…

Machine Learning · Computer Science 2023-04-12 Qunxi Zhu , Yao Guo , Wei Lin

Real-world lighting often consists of multiple illuminants with different spectra. Separating and manipulating these illuminants in post-process is a challenging problem that requires either significant manual input or calibrated scene…

Computer Vision and Pattern Recognition · Computer Science 2017-11-28 Zhuo Hui , Kalyan Sunkavalli , Sunil Hadap , Aswin C. Sankaranarayanan

In 1950 Edward Nelson asked the following simple-sounding question: \emph{How many colors are needed to color the Euclidean plane $\mathbb{E}^2$ such that no two points distance $1$ apart are identically colored?} We say that $1$ is a…

Combinatorics · Mathematics 2018-05-17 Geoffrey Exoo , Dan Ismailescu

In a previous paper we have described a technique to derive constraints on the differential emission measure (DEM) distribution, a measure of the temperature distribution, of collisionally ionized hot plasmas from their X-ray emission line…

Astrophysics · Physics 2009-11-10 Patrick S. Wojdowski , Norbert S. Schulz

We present an approach that improves the search for reliable astrophysical parameters (e.g. age, mass, and distance) of differentially-reddened, pre-main sequence-rich star clusters. It involves simulating conditions related to the…

Astrophysics of Galaxies · Physics 2015-06-03 Charles Bonatto , Eduardo Bica , Eliade F. Lima

We consider the coloring of certain distance graphs on the Euclidean plane. Namely, we ask for the minimal number of colors needed to color all points of the plane in such a way that pairs of points at distance in the interval $[1,b]$ get…

Combinatorics · Mathematics 2022-01-13 Joanna Chybowska-Sokół , Konstanty Junosza-Szaniawski , Krzysztof Węsek

During the last decade, hyperspectral images have attracted increasing interest from researchers worldwide. They provide more detailed information about an observed area and allow an accurate target detection and precise discrimination of…

Computer Vision and Pattern Recognition · Computer Science 2022-10-26 Asma Elmaizi , Hasna Nhaila , Elkebir Sarhrouni , Ahmed Hammouch , Nacir Chafik

This paper describes several improvements to a new method for signal decomposition that we recently formulated under the name of Differentiable Dictionary Search (DDS). The fundamental idea of DDS is to exploit a class of powerful deep…

Audio and Speech Processing · Electrical Eng. & Systems 2022-11-29 Lukáš Samuel Marták , Rainer Kelz , Gerhard Widmer

Partial Differential Equations (PDEs) have long been recognized as powerful tools for image processing and analysis, providing a framework to model and exploit structural and geometric properties inherent in visual data. Over the years,…

Image and Video Processing · Electrical Eng. & Systems 2024-12-17 Alejandro Garnung Menéndez

Singular values are used to construct physically admissible 3-dimensional mixing matrices characterized as contractions. Depending on the number of singular values strictly less than one, the space of the 3-dimensional mixing matrices can…

High Energy Physics - Phenomenology · Physics 2020-04-22 Wojciech Flieger , Janusz Gluza , Kamil Porwit

Worldwide efforts are underway to detect neutrinoless double beta ($0\nu\beta\beta$) decay using experiments based on various technologies and target isotopes. Future experiments in this regard aim to exclude the inverted order (IO)…

Nuclear Experiment · Physics 2025-09-30 X. Yu , L. T. Yang , Q. Yue , H. Ma , H. T. Wong

We report on two-photon interferences from highly indistinguishable single photons emitted by a quantum dot. Stricly resonant excitation with picosecond laser pulses allows coherent state preparation with a signifi- cantly increased…

Mesoscale and Nanoscale Physics · Physics 2014-09-02 Léonard Monniello , Antoine Reigue , Richard Hostein , Aristide Lemaitre , Anthony Martinez , Roger Grousson , Valia Voliotis