Results 81 to 90 of about 59,513 (222)

Balancing Reconstruction Error and Kullback-Leibler Divergence in Variational Autoencoders

IEEE Access, 2020
Likelihood-based generative frameworks are receiving increasing attention in the deep learning community, mostly on account of their strong probabilistic foundation.
Andrea Asperti, Matteo Trentin
doaj   +1 more source

Notes on Kullback-Leibler Divergence and Likelihood

CoRR, 2014
The Kullback-Leibler (KL) divergence is a fundamental equation of information theory that quantifies the proximity of two probability distributions. Although difficult to understand by examining the equation, an intuition and understanding of the KL divergence arises from its intimate relationship with likelihood theory.
openaire   +2 more sources

Inverse sky islands: lowland river valleys drive microbial divergence while high elevations select for convergence in massive mountain ecosystems

Ecography, EarlyView.
Mountain ecosystems are often interpreted through the lens of the ‘sky island' model, where high‐elevation habitats function as isolated archipelagos. However, this model's applicability to massive, topographically complex mountain ranges where highlands are continuous and lowlands are fragmented remains untested.
Yazhou Zhang, J. Aaron Hogan, Jianjun Wang, Wenguang Sun, Yaojun Ye, Xin Liu, Minshu Song, Hang Sun   +7 more
wiley   +1 more source

The McMillan Theorem for Colored Branching Processes and Dimensions of Random Fractals

Entropy, 2014
For the simplest colored branching process, we prove an analog to the McMillan theorem and calculate the Hausdorff dimensions of random fractals defined in terms of the limit behavior of empirical measures generated by finite genetic lines.
Victor Bakhtin
doaj   +1 more source

A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios

Journal of Forecasting, EarlyView.
ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley   +1 more source

Lost in Translation? Risk‐Adjusting RMSE for Economic Forecast Performance

Journal of Forecasting, EarlyView.
ABSTRACT When used for parameter optimization and/or model selection, traditional mean squared error (MSE)–based measures of forecast accuracy often exhibit a weak or even negative correlation with the economic value of return forecasts measured by, for example, the Sharpe ratios of the resulting portfolios.
Lukas Salcher, Sebastian Stöckl, Michael Hanke   +2 more
wiley   +1 more source

Fendioxypyracil, a new and systemic PPO‐inhibiting herbicide for X‐spectrum weed control

Pest Management Science, EarlyView.
This graphical abstract presents the discovery and synthesis of PPO herbicide structures with a central pyridine core, showing molecular conformations, dose–response inhibition curves for PPO1 and PPO2, and comparative weed and grass control efficacy of fendioxypyracil versus other herbicides in greenhouse and field trials.
Tobias Seiser, Aimone Porri, Philipp Johnen, Silke Zeyer, Judith Wahrheit, Michael Betz, Breght Vandenberghe, Scott Asher, Liliana Parra Rapado   +8 more
wiley   +1 more source

Efficient ECG classification based on the probabilistic Kullback-Leibler divergence

Informatics in Medicine Unlocked
Diagnostic systems of cardiac arrhythmias face early and accurate detection challenges due to the overlap of electrocardiogram (ECG) patterns. Additionally, these systems must manage a huge number of features.
Dhiah Al-Shammary, Mohammed Radhi, Ali Hakem AlSaeedi, Ahmed M. Mahdi, Ayman Ibaida, Khandakar Ahmed   +5 more
doaj   +1 more source

A generalization of the Kullback–Leibler divergence and its properties [PDF]

Journal of Mathematical Physics, 2009
A generalized Kullback–Leibler relative entropy is introduced starting with the symmetric Jackson derivative of the generalized overlap between two probability distributions. The generalization retains much of the structure possessed by the original formulation.
openaire   +3 more sources

A structurally localized ensemble Kalman filtering approach

Quarterly Journal of the Royal Meteorological Society, EarlyView.
We derive an inherently localized ensemble Kalman filtering (EnKF) approach, avoiding the need for any auxiliary localization technique. The idea is to first use the variational Bayesian optimization to approximate the (continuous) state analysis probability density function (pdf) by a product of independent marginal pdfs corresponding to small ...
Boujemaa Ait‐El‐Fquih, Ibrahim Hoteit   +1 more
wiley   +1 more source