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Explainable Deep Learning Models for Dynamic and Online Malware Classification.

, , , , and . SMARTCOMP, page 182-189. IEEE, (2024)

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Asynchronous Gibbs Sampling., , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 144-154. PMLR, (2020)The Experiment is just as Important as the Likelihood in Understanding the Prior: a Cautionary Note on Robust Cognitive Modeling, , and . Computational Brain & Behavior, 2 (3): 210--217 (Dec 1, 2019)Bayesian computing with INLA: New features., , , and . Comput. Stat. Data Anal., (2013)Using stacking to average Bayesian predictive distributions, , , and . (2017)cite arxiv:1704.02030.Validating Bayesian Inference Algorithms with Simulation-Based Calibration, , , , and . (2018)cite arxiv:1804.06788Comment: 26 pages, 14 figures.Explainable Deep Learning Models for Dynamic and Online Malware Classification., , , , and . SMARTCOMP, page 182-189. IEEE, (2024)The Integrated Nested Laplace Approximation for Fitting Dirichlet Regression Models., , , , and . J. Comput. Graph. Stat., 32 (3): 805-823 (2023)Multivariate Gaussian Random Fields Using Systems of Stochastic Partial Differential Equations, , , and . (2013)cite arxiv:1307.1379Comment: 47 pages, 19 figures.Constructing Priors that Penalize the Complexity of Gaussian Random Fields, , , and . (2015)cite arxiv:1503.00256.Hamiltonian Monte Carlo using an embedded Laplace approximation, , , and . (2020)cite arxiv:2004.12550Comment: 16 pages, 12 figures.