Prediction uncertainty computed from the entropy
An Analysis of States in the Phase Space: Uncertainty, Entropy and Diffusion
... is the velocity with which the particle travels within ∆x. No hypothesis is required about the ranges that quantify the con- cepts of space and time uncertainty. Their sizes, in principle arbitrary, can vary ...
11
Matrix Game Under Uncertainty Theory Via Entropy
... diversity from one generation of a population of genetic algorithm chromosomes to the ...chromosome from its initial ...entirely from the previous ...
18
Entropy for business failure prediction : an improved prediction model for the construction industry
... affect prediction models based on dis- criminant ...time-series prediction test and the need for a prior probability of failure; however, it is not always easy to find any estimate for the prior probability ...
16
Entropy-based approach to missing-links prediction
... relationships from the observed network ...links prediction. Here, we propose an entropy-based method to predict a given percentage of missing links, by identifying them with the most probable ...
15
From Credit Assignment to Entropy Regularization: Two New Algorithms for Neural Sequence Prediction
... fer from the exposure bias, which refers to the phenomenon that the model is never exposed to its own failures during training, and thus cannot recover from an error at test ...roots from the ...
11
Optimization of Item Selection with Prediction Uncertainty
... estimated from prediction ...model prediction under the low-latency ...good prediction accuracy, the models used in industry are getting more and more complex, ...subset from all ...
89
Decreasing uncertainty in planning with state prediction
... Figure 6: Mean confidence values from 10-cross-fold validation for 20 objects. The x axis representation is logarithmic. 40 objects in the each problem domain only 8% of known data is enough for accuracy over 90%. ...
7
On the sources of hydrological prediction uncertainty in the Amazon
... arise from uncertainty on (i) model structure and parameters, (ii) atmospheric forcing such as precipitation and (iii) initial states ...range from simple climatology to an ensemble of histori- cal ...
11
Adding Model Uncertainty to Depth Prediction
... Dropout [23] is a technique for addressing overfitting in neural networks. Over- fitting is a modeling error where the network can accurately predict on the train- ing dataset but cannot predict unseen data, and is ...
28
Maximum entropy prior uncertainty and correlation of statistical economic data
... to uncertainty (stemming from measurement errors or confi- dentiality) but information concerning that uncertainty is often ...concepts from Bayesian inference and the maximum entropy ...
12
Russian Stress Prediction using Maximum Entropy Ranking
... expanded from Zaliznyak’s Grammatical Dictionary of the Russian Lan- guage (Zaliznyak, ...derive from lemmata from which some training data forms are also de- ...
5
A Maximum Entropy Classifier for Cross Lingual Pronoun Prediction
... learn from much smaller data sets. Incorporating more train- ing data from the Europarl corpus could alleviate this problem and would make it possible to deter- mine whether these differences ...
7
The Entropy and PCA Based Anomaly Prediction in Data Streams
... points accompanied special characteristics, such as transiency, uncertainty, dynamic data distribution, multidimensionality, and dynamic relationship. The arrival rate of data stream is usually high and the ...
8
Stopping-power prediction with dual-energy computed tomography
... A clinical trial is currently underway at DKFZ to investigate patient treatment planning based on contrast-enhanced DECT. 5.4.2 Measurement of I-values The developed experimental setup [IIa] can be used for the ...
71
A Bayesian Monte-Carlo Uncertainty Model for Assessment of Shear Stress Entropy
... derived from all four entropy models, as illustrated in Figure ...Renyi entropy model is higher than those of the Shannon, Shannon PL, and Tsallis ...Renyi entropy is much higher than other ...
47
Epistemological Limits to Scientific Prediction: The Problem of Uncertainty
... scientific prediction from the two settled view- points: “barriers” and ...so from some clear coordinates: he proposes an approach where the internal elements have primacy over the external factors ...
9
Parametric Uncertainty in Numerical Weather Prediction Models
... generally involves arduous tuning of the model by hand (see e.g. Mauritsen et al., 2012). Thus, algorithmic tools would (i) help in making the process faster, and moreover (ii) produce a more realistic model ...
56
Uncertainty-Aware Attention for Reliable Interpretation and Prediction
... sepsis prediction in ICU and disease risk prediction from electronic health records (EHR) that have large degree of uncertainties in the input, on which our model outperforms the baseline attention ...
27
On the prediction and the formation of the sigma phase in CrMnCoFeNix high entropy alloys
... high entropy alloys necessitates the use of computational methods when attempting to optimise for any given ...dramatically from the experimentally observed microstructures, indicating that the underlying ...
12
Computed tomography scan based prediction of the vulnerable carotid plaque
... Regarding information bias, such bias is possible re- garding our histological analysis. IPH was used as a pragmatic definition of a vulnerable plaque due to its strong association to such [11], and the larger observer ...
8