Probabilistic trajectory prediction with Gaussian mixture models
In the context of driver assistance, an accurate and reliable prediction of the vehicle's
trajectory is beneficial. This can be useful either to increase the flexibility of comfort systems …
trajectory is beneficial. This can be useful either to increase the flexibility of comfort systems …
Improving skin cancer classification using heavy-tailed Student t-distribution in generative adversarial networks (TED-GAN)
Deep learning has gained immense attention from researchers in medicine, especially in
medical imaging. The main bottleneck is the unavailability of sufficiently large medical …
medical imaging. The main bottleneck is the unavailability of sufficiently large medical …
On the Conditional Distribution of the Multivariate t Distribution
P Ding - The American Statistician, 2016 - Taylor & Francis
As alternatives to the normal distributions, t distributions are widely applied in robust
analysis for data with outliers or heavy tails. The properties of the multivariate t distribution …
analysis for data with outliers or heavy tails. The properties of the multivariate t distribution …
Best integer equivariant estimation for elliptically contoured distributions
PJG Teunissen - Journal of Geodesy, 2020 - Springer
This contribution extends the theory of integer equivariant estimation (Teunissen in J
Geodesy 77: 402–410, 2003) by developing the principle of best integer equivariant (BIE) …
Geodesy 77: 402–410, 2003) by developing the principle of best integer equivariant (BIE) …
A score-driven conditional correlation model for noisy and asynchronous data: An application to high-frequency covariance dynamics
The analysis of the intraday dynamics of covariances among high-frequency returns is
challenging due to asynchronous trading and market microstructure noise. Both effects lead …
challenging due to asynchronous trading and market microstructure noise. Both effects lead …
Best integer equivariant position estimation for multi-GNSS RTK: A multivariate normal and t-distributed performance comparison
R Odolinski, PJG Teunissen - Journal of Geodesy, 2022 - Springer
The best integer equivariant (BIE) estimator for the multivariate t-distribution was introduced
in Teunissen (J Geod, 2020. https://doi. org/10.1007/s00190-020-01407-2), where it was …
in Teunissen (J Geod, 2020. https://doi. org/10.1007/s00190-020-01407-2), where it was …
Generative adversarial networks with mixture of t-distributions noise for diverse image generation
Image generation is a long-standing problem in the machine learning and computer vision
areas. In order to generate images with high diversity, we propose a novel model called …
areas. In order to generate images with high diversity, we propose a novel model called …
On global convergence of ResNets: From finite to infinite width using linear parameterization
Overparameterization is a key factor in the absence of convexity to explain global
convergence of gradient descent (GD) for neural networks. Beside the well studied lazy …
convergence of gradient descent (GD) for neural networks. Beside the well studied lazy …
Residual projection for quantile regression in vertically partitioned big data
Standard regression techniques model only the mean of the response variable. Quantile
regression (QR) is more powerful in that it depicts a comprehensive relationship between …
regression (QR) is more powerful in that it depicts a comprehensive relationship between …
Sufficient reductions in regressions with elliptically contoured inverse predictors
There are two general approaches based on inverse regression for estimating the linear
sufficient reductions for the regression of Y on X: the moment-based approach such as SIR …
sufficient reductions for the regression of Y on X: the moment-based approach such as SIR …