Variable kernel density estimation

By Martin L. Hazelton. 2003

520 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Statistics and Probability

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In Civil and Structural Engineering

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Citations in the corpus

Unbounded cache model for online language modeling with open vocabulary (2017, methodology): “This estimator is known as variable kernel density estimation [51].”
Fast AutoAugment (2019, methodology): “We employ variable kernel density estimation [33] on graph-structured search space S to approximate the criterion (3). tree-structured Practically, since the optimization method is already proposed in tree-structured Parzen estimator (TPE) algorithm [1], we apply their HyperOpt library for the…”
One-Class Support Measure Machines for Group Anomaly Detection (2013, methodology): “The second type of VKDE is a sample smoothing estimator (Terrell and Scott 1992).”
Noise Estimation Using Density Estimation for Self-Supervised Multimodal Learning (2020, methodology): “Existing density estimation algorithms can be divided into two categories: (a) parametric or semi-parametric approaches such as Gaussian Mixture models (McLachlan and Krishnan 2007; Wang and Wang 2015) and probabilistic graphical models (Koller and Friedman 2009); and (b) non-parametric approaches s”
The Generalized Cross Entropy Method, with Applications to Probability Density Estimation (2011, unknown): “, [14], [39], [37], [52], [35], [59], [1]).”
Prosospeech: Enhancing Prosody with Quantized Vector Pre-Training in Text-To-Speech (2022, background): “…pitch DTW )) / S W , where W is the Chinese character dictionary, KL ( · ) calculates the KL-divergence, KDE ( · ) is the kernel density estimation [24] function smoothing the discrete distribution and converting it to continuous distribution, d wi is the duration discrete distribution of word w…”
Bivariate frequency analysis of floods using a diffusion based kernel density estimator (2013, methodology): “…1994], and use of nonconventional kernels such as beta kernels [e.g., Chen, 1999, 2000; Bouezmarni and Scaillet, 2003], gamma kernels [e.g., Bouezmarni and Rombouts, 2009], boundary kernels [e.g., Gasser and M€uller, 1979], and adaptive kernels [e.g., Terrell and Scott, 1992; Botev et al., 2010].”
Multiple-instance discriminant analysis (2014, methodology): “We utilize kernel density estimation [39,40] to initialize positive prototypes.”
A Big Data Analytics Method for Tourist Behaviour Analysis (2017, unknown): “Kernel Density Estimation (KDE): KDE is a non-parametric method to estimate the probability density function of a random variable [63].”
A tutorial on kernel density estimation and recent advances (2017, methodology): “In the former case, we use h = h(x) so KDE becomes bpn x ð Þ 1⁄4 1 nhd x ð ÞPni1⁄41 K x Xi h x ð Þ ; which is referred to as the balloon estimator [6].”
DiffProsody: Diffusion-Based Latent Prosody Generation for Expressive Speech Synthesis With Prosody Conditional Adversarial Training (2023, methodology): “We then binned the entire range into 100 bins and applied a kernel density estimation [57] to each bin to calculate the KL D for a smoothed distribution.”
A smoothed backbone-dependent rotamer library for proteins derived from adaptive kernel density estimates and regressions (2011, unknown): “Terrell, G.R., and Scott, D.W. (1992).”