Results 81 to 90 of about 2,386,323 (274)

Contrasting probabilistic scoring rules [PDF]

, 2013
There are several scoring rules that one can choose from in order to score probabilistic forecasting models or estimate model parameters. Whilst it is generally agreed that proper scoring rules are preferable, there is no clear criterion for preferring ...
Machete, Reason, Machete, Reason L.
core   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Recent Advances in Probabilistic Electricity Price Forecasting: A Review of Methods and Evaluation Metrics

Energies
Electricity price forecasting has traditionally relied on point predictions, which provide a single expected value for each future delivery period. However, the high volatility, spikes, heavy tails, negative prices and regime changes observed in modern ...
Grzegorz Dudek, Paweł Piotrowski, Marcin Kopyt, Dariusz Baczyński   +3 more
doaj   +1 more source

Objective Bayesian inference with proper scoring rules [PDF]

, 2018
Standard Bayesian analyses can be difficult to perform when the full likelihood, and consequently the full posterior distribution, is too complex or even impossible to specify or if robustness with respect to data or to model misspecifications is ...
E. Ruli, L. Ventura, Federica Giummole', Laura Ventura, F. Giummole', Giummolè, F., Erlis Ruli, F. Giummolè, Ventura, L., Mameli, V., V. Mameli, Valentina Mameli, Ruli, E.   +12 more
core   +1 more source

Spatially Controlled Embedded Bioprinting of Prevascularized Spheroids‐Containing Biopatch Enables Functional Skin Regeneration

Advanced Healthcare Materials, EarlyView.
A spatially controlled embedded bioprinting strategy enables precise engineering of prevascularized multicellular spheroids within skin‐derived dECM bioinks. Optimized spheroid size, composition, and spacing promote vascular maturation, paracrine signaling, and tissue integration, resulting in enhanced angiogenesis, blood perfusion, and functional skin
Minjun Ahn, Gyu Tae Park, Dongjun Lee, Sik Yoon, Sae‐Ock Oh, Jae Ho Kim, Byoung Soo Kim   +6 more
wiley   +1 more source

Bayesian Model Selection Based on Proper Scoring Rules

Bayesian Analysis, 2015
Published at http://dx.doi.org/10.1214/15-BA942 in the Bayesian Analysis (http://projecteuclid.org/euclid.ba) by the International Society of Bayesian Analysis (http://bayesian.org/)
Philip Dawid, A., MUSIO, MONICA
openaire   +4 more sources

Survival Regression with Proper Scoring Rules and Monotonic Neural Networks

, 2021
We consider frequently used scoring rules for right-censored survival regression models such as time-dependent concordance, survival-CRPS, integrated Brier score and integrated binomial log-likelihood, and prove that neither of them is a proper scoring rule. This means that the true survival distribution may be scored worse than incorrect distributions,
Rindt, D, Hu, R, Steinsaltz, D, Sejdinovic, D   +3 more
openaire   +4 more sources

Evaluating probability forecasts in terms of refinement and strictly proper scoring rules [PDF]

This note gives an easily verified necessary and sufficient condition for one probability forecaster to empirically outperform another one in terms of all strictly proper scoring rules.
Krämer, Walter
core  

A truth serum for non-Bayesians : correcting proper scoring rules for risk attitudes [PDF]

, 2009
Proper scoring rules provide convenient and highly efficient tools for incentive-compatible elicitations of subjective beliefs. As traditionally used, however, they are valid only under expected value maximization.
JOEP SONNEMANS, van de Kuilen, G., Offerman, T, Offerman, T., THEO OFFERMAN, Wakker, Peter, Wakker, P.P., Sonnemans, J, van de Kuilen, G, PETER P. WAKKER, Sonnemans, J., Offerman, T.J.S., van de Kuilen, G.; id_orcid, GIJS VAN DE KUILEN, Sonnemans, J.J., Offerman, T.; id_orcid   +15 more
core   +2 more sources

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source