Results 121 to 130 of about 2,509,053 (235)
Proceedings, 2017 Shape Analysis studies geometrical objects, as for example a flat fish in the plane or a human head in the space. The applications range from structural biology, computer vision, medical imaging to archaeology. We focus on the selection of an appropriate
Angela De Sanctis, Stefano A. Gattone
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Differentially Private Sliced Wasserstein Distance
, 2021 Developing machine learning methods that are privacy preserving is today a central topic of research, with huge practical impacts. Among the numerous ways to address privacy-preserving learning, we here take the perspective of computing the divergences between distributions under the Differential Privacy (DP) framework -- being able to compute ...
Rakotomamonjy, Alain, Ralaivola, Liva
openaire +3 more sources
Validation of machine learning based scenario generators
Journal of Risk and Insurance, EarlyView.Abstract Machine learning (ML) methods are becoming increasingly important for designing economic scenario generators for internal models. Validating data‐driven models requires different methods than validating classical, theory‐based models. We discuss two novel aspects of such validation: first, checking the multivariate distribution of risk factors,
Gero Junike, Solveig Flaig, Ralf Werner
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Wasserstein Distance Maximizing Intrinsic Control
, 2021 This paper deals with the problem of learning a skill-conditioned policy that acts meaningfully in the absence of a reward signal. Mutual information based objectives have shown some success in learning skills that reach a diverse set of states in this setting.
Durugkar, Ishan +3 more
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Density‐Valued ARMA Models by Spline Mixtures
Journal of Time Series Analysis, EarlyView.ABSTRACT This paper proposes a novel framework for modeling time series of probability density functions by extending autoregressive moving average (ARMA) models to density‐valued data. The method is based on a transformation approach, wherein each density function on a compact domain [0,1]d$$ {\left[0,1\right]}^d $$ is approximated by a B‐spline ...
Yasumasa Matsuda, Rei Iwafuchi
wiley +1 more source
An alternating multiple residual Wasserstein regularization model for Gaussian image denoising
Scientific ReportsResidual histograms can provide meaningful statistical information in low-level visual research. However, the existing image denoising methods do not deeply explore the potential of alternate multiple residual histograms for overall optimization ...
Ruiqiang He +4 more
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Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach
, 2018 Bayesian inference typically requires the computation of an approximation to the posterior distribution. An important requirement for an approximate Bayesian inference algorithm is to output high-accuracy posterior mean and uncertainty estimates ...
Broderick, Tamara +3 more
core
Testing Distributional Granger Causality With Entropic Optimal Transport
Journal of Time Series Analysis, EarlyView.ABSTRACT We develop a novel nonparametric test for Granger causality in distribution based on entropic optimal transport. Unlike classical mean‐based approaches, the proposed method directly compares the full conditional distributions of a response variable with and without the history of a candidate predictor.
Tao Wang
wiley +1 more source
S2‐PepAnalyst: A Web Tool for Predicting Plant Small Signalling Peptides
Plant Biotechnology Journal, EarlyView.ABSTRACT Small signalling peptides (SSPs) serve as crucial mediators of cell‐to‐cell communication in plants, orchestrating diverse physiological processes from development to stress responses. While recent advances in sequencing technologies have improved genome annotation, the identification of novel SSPs remains challenging due to their small size ...
Kelly L. Vomo‐Donfack +5 more
wiley +1 more source
International Journal of Electrical Power & Energy SystemsWith the rapid expansion of large-scale clean energy bases in major energy-producing countries, high-quality scenario generation has become essential for effective energy management and intelligent scheduling.
Bo Wu +7 more
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