Results 11 to 20 of about 11,165,306 (334)
ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation [PDF]
Neural Information Processing Systems, 2023 Score distillation sampling (SDS) has shown great promise in text-to-3D generation by distilling pretrained large-scale text-to-image diffusion models, but suffers from over-saturation, over-smoothing, and low-diversity problems. In this work, we propose
Zhengyi Wang +6 more
semanticscholar +1 more source
Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation [PDF]
Computer Vision and Pattern Recognition, 2022 A diffusion model learns to predict a vector field of gradients. We propose to apply chain rule on the learned gradients, and back-propagate the score of a diffusion model through the Jacobian of a differentiable renderer, which we instantiate to be a ...
Haochen Wang +4 more
semanticscholar +1 more source
BMC Genomics, 2020 To evaluate binary classifications and their confusion matrices, scientific researchers can employ several statistical rates, accordingly to the goal of the experiment they are investigating.
D. Chicco, Giuseppe Jurman
semanticscholar +1 more source
The Vendi Score: A Diversity Evaluation Metric for Machine Learning [PDF]
Trans. Mach. Learn. Res., 2022 Diversity is an important criterion for many areas of machine learning (ML), including generative modeling and dataset curation. However, existing metrics for measuring diversity are often domain-specific and limited in flexibility.
Dan Friedman, A. B. Dieng
semanticscholar +1 more source
Score-based diffusion models for accelerated MRI [PDF]
Medical Image Anal., 2021 Score-based diffusion models provide a powerful way to model images using the gradient of the data distribution. Leveraging the learned score function as a prior, here we introduce a way to sample data from a conditional distribution given the ...
Hyungjin Chung, Jong-Chul Ye
semanticscholar +1 more source
Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2019 Recently, increasing attention has been drawn to the internal mechanisms of convolutional neural networks, and the reason why the network makes specific decisions.
Haofan Wang +7 more
semanticscholar +1 more source
Asymptotic optimality of the quasi-score estimator in a class of linear score estimators [PDF]
, 2006 We prove that the quasi-score estimator in a mean-variance model is optimal in the class of (unbiased) linear score estimators, in the sense that the difference of the asymptotic covariance matrices of the linear score and quasi-score estimator is ...
Kukush, Alexander, Schneeweiß, Hans
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Multivariate Behavioral Research, 2011 The propensity score is the probability of treatment assignment conditional on observed baseline characteristics. The propensity score allows one to design and analyze an observational (nonrandomized) study so that it mimics some of the particular ...
P. Austin
semanticscholar +1 more source
Simple new risk score model for adult cardiac extracorporeal membrane oxygenation: simple cardiac ECMO score. [PDF]
, 2015 BACKGROUND: Although the use of cardiac extracorporeal membrane oxygenation (ECMO) is increasing in adult patients, the field lacks understanding of associated risk factors. While standard intensive care unit risk scores such as SAPS II (simplified acute
Cavarocchi, Nicholas +3 more
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Statistics in Medicine, 2009 The propensity score is a subject's probability of treatment, conditional on observed baseline covariates. Conditional on the true propensity score, treated and untreated subjects have similar distributions of observed baseline covariates.
P. Austin
semanticscholar +1 more source