UNBIASED PARAMETER INFERENCE FOR A CLASS OF PARTIALLY OBSERVED LÉVY-PROCESS MODELS.
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- Foundations of Data Science, 2022, v. 4, n. 2, p. 299, doi. 10.3934/fods.2022008
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Works matching IS 26398001 AND DT 2022 AND VI 4 AND IP 2
Results: 5
1
2
MEAN-FIELD AND KINETIC DESCRIPTIONS OF NEURAL DIFFERENTIAL EQUATIONS.
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- Foundations of Data Science, 2022, v. 4, n. 2, p. 271, doi. 10.3934/fods.2022007
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3
GEOMETRY AND GENERALIZATION: EIGENVALUES AS PREDICTORS OF WHERE A NETWORK WILL FAIL TO GENERALIZE.
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- Foundations of Data Science, 2022, v. 4, n. 2, p. 217, doi. 10.3934/fods.2022004
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- Article
4
ASPECTS OF TOPOLOGICAL APPROACHES FOR DATA SCIENCE.
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- Foundations of Data Science, 2022, v. 4, n. 2, p. 165, doi. 10.3934/fods.2022002
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5
ANAPT: ADDITIVE NOISE ANALYSIS FOR PERSISTENCE THRESHOLDING.
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- Foundations of Data Science, 2022, v. 4, n. 2, p. 243, doi. 10.3934/fods.2022005
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- Article