Results 71 to 80 of about 297,382 (270)

Diffusion model conditioning on Gaussian mixture model and negative Gaussian mixture gradient

Neurocomputing
Diffusion models (DMs) are a type of generative model that has a huge impact on image synthesis and beyond. They achieve state-of-the-art generation results in various generative tasks. A great diversity of conditioning inputs, such as text or bounding boxes, are accessible to control the generation.
Weiguo Lu, Xuan Wu, Deng Ding, Jinqiao Duan, Jirong Zhuang, Gangnan Yuan   +5 more
openaire   +2 more sources

A Fast Incremental Gaussian Mixture Model

PLOS ONE, 2015
Ce travail s'appuie sur les efforts antérieurs en matière d'apprentissage incrémentiel en ligne, à savoir le Incremental Gaussian Mixture Network (IGMN). L'IGMN est capable d'apprendre des flux de données en une seule passe en améliorant son modèle après avoir analysé chaque point de données et l'avoir jeté par la suite.
Rafael Pinto, Paulo Martins Engel
openaire   +5 more sources

Flexibility and Dynamicity Enhances and Controls Supramolecular Self‐Assembly of Zinc(II) Metallogels

Advanced Functional Materials, EarlyView.
Zinc(II) coordination complexes with tunable aryloxy‐imine ligands exhibit controllable supramolecular self‐assembly into hierarchical fibrous structures. Coordination‐driven stacking, not π–π interactions, enables gelation, dynamic assembly/disassembly, and enhanced nanomechanical properties.
Merlin R. Stühler, Hesam Makki, Dorothee Silbernagl, Mathias Dimde, Kai Ludwig, Bengt E. Tegner, Christopher Greve, Konstantin Rausch, Eva M. Herzig, Anna Köhler, Alex J. Plajer   +10 more
wiley   +1 more source

GMCM: Unsupervised Clustering and Meta-Analysis Using Gaussian Mixture Copula Models

Journal of Statistical Software, 2016
Methods for clustering in unsupervised learning are an important part of the statistical toolbox in numerous scientific disciplines. Tewari, Giering, and Raghunathan (2011) proposed to use so-called Gaussian mixture copula models (GMCM) for general ...
Anders Ellern Bilgrau, Poul Svante Eriksen, Jakob Gulddahl Rasmussen, Hans Erik Johnsen, Karen Dybkaer, Martin Boegsted   +5 more
doaj   +1 more source

Large Scale Clustering with Variational EM for Gaussian Mixture Models

, 2019
How can we efficiently find large numbers of clusters in large data sets with high-dimensional data points? Our aim is to explore the current efficiency and large-scale limits in fitting a parametric model for clustering to data distributions.
Forster, Dennis, Hirschberger, Florian, Lücke, Jörg   +2 more
core   +1 more source

Bayesian approaches to Gaussian mixture modeling

IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998
A Bayesian-based methodology is presented which automatically penalizes overcomplex models being fitted to unknown data. We show that, with a Gaussian mixture model, the approach is able to select an "optimal" number of components in the model and so partition data sets.
Roberts, S, Husmeier, D, Rezek, I, Penny, W   +3 more
openaire   +2 more sources

Modulating Electrochemical CO2 Reduction Pathways via Interfacial Electric Field

Advanced Functional Materials, EarlyView.
Engineering interfacial electric fields in Cu/ITO electrodes enables precise control of CO2 reduction pathways. Charge transfer from Cu to ITO generates positively charged Cu species that steer selectivity from ethylene toward methane. This work demonstrates how interfacial electric‐field modulation can direct reaction intermediates and transform ...
Mahdi Salehi, Zhengyuan Gao, Sai Phani Kumar Vangala, Amirhossein Farzi, Hamed Heidarpour, Morgan McKee, Nikolay Kornienko, Ali Seifitokaldani   +7 more
wiley   +1 more source

A new method of peak detection for analysis of comprehensive two-dimensional gas chromatography mass spectrometry data

, 2014
We develop a novel peak detection algorithm for the analysis of comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC$\times$GC-TOF MS) data using normal-exponential-Bernoulli (NEB) and mixture probability models.
Jeong, Jaesik, Kim, Seongho, Ouyang, Ming, Shen, Changyu, Zhang, Xiang   +4 more
core   +1 more source

Positive‐Tone Nanolithography of Antimony Trisulfide with Femtosecond Laser Wet‐Etching

Advanced Functional Materials, EarlyView.
A butyldithiocarbamic acid (BDCA) etchant is used to fabricate various micro‐ and nanoscale structures on amorphous antimony trisulfide (a‐Sb2S3) thin film via femtosecond laser etching. Numerical analysis and experimental results elucidate the patterning mechanism on gold (reflective) and quartz (transmissive) substrates.
Abhrodeep Dey, Uwe Hübner, Albane Benardais, Xiaofei Wu, Andrea Dellith, Jan Dellith, Torsten Wieduwilt, Henrik Schneidewind, Markus A Schmidt, Virginie Nazabal, Volker Deckert, Jer‐Shing Huang, Wei Wang   +12 more
wiley   +1 more source

Fast‐Responding O2 Gas Sensor Based on Luminescent Europium Metal‐Organic Frameworks (MOF‐76)

Advanced Functional Materials, EarlyView.
Luminescent MOF‐76 materials based on Eu(III) and mixed Eu(III)/Y(III) show rapid and reversible changes in emission intensity in response to O2 with very short response times. The effect is based on triplet quenching of the linker ligands that act as photosensitizers. Average emission lifetimes of a few milliseconds turn out to be mostly unaffected by
Zhenyu Zhao, Christian Weinberger, Jakob Steube, Matthias Bauer, Martin Brehm, Michael Tiemann   +5 more
wiley   +1 more source