Observational Equivalence of Conditional Belief Bases
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2023 In nonmonotonic reasoning, a conditional of the form ‘If A then usually B’ is typically accepted if a situation where both A and B hold is deemed to be more plausible, more probable, or less surprising, etc., than a situation where A holds, but B does ...
Christoph Beierle +2 more
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Normal Forms of Conditional Belief Bases Respecting Inductive Inference
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022 Normal forms of syntactic entities play an important role in many different areas in computer science. In this paper, we address the question of how to obtain normal forms and minimal normal forms of conditional belief bases in order to, e.g., ease ...
Christoph Beierle, Jonas Haldimann
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Inference of cosmic-ray source properties by conditional invertible neural networks
European Physical Journal C: Particles and Fields, 2022 The inference of physical parameters from measured distributions constitutes a core task in physics data analyses. Among recent deep learning methods, so-called conditional invertible neural networks provide an elegant approach owing to their probability-
Teresa Bister +3 more
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Bayesian inference for the log-symmetric autoregressive conditional duration model
Anais da Academia Brasileira de Ciências, 2021 This paper adapts Hamiltonian Monte Carlo methods for application in log-symmetric autoregressive conditional duration models. These recent models are based on a class of log-symmetric distributions. In this class, it is possible to model both median and
JEREMIAS LEÃO +3 more
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cglasso: An R Package for Conditional Graphical Lasso Inference with Censored and Missing Values
Journal of Statistical Software, 2023 Sparse graphical models have revolutionized multivariate inference. With the advent of high-dimensional multivariate data in many applied fields, these methods are able to detect a much lower-dimensional structure, often represented via a sparse ...
Luigi Augugliaro +3 more
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Empirical likelihood inference for threshold autoregressive conditional heteroscedasticity model
Journal of Inequalities and Applications, 2021 This paper considers the parameter estimation problem of a first-order threshold autoregressive conditional heteroscedasticity model by using the empirical likelihood method.
Cuixin Peng, Zhiwen Zhao
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Semantic Classification of Conditional Construction in Persian Language [PDF]
̒Ilm-i Zabān, 2020 Conditional constructions consist of two clauses. The existence or non-existence of a causal relationship between these two clauses causes the conditional construction to be divided into two groups: consequential and non- consequential conditionals.
Azadeh Mirzaei
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Tractability through Exchangeability: A New Perspective on Efficient Probabilistic Inference [PDF]
, 2014 Exchangeability is a central notion in statistics and probability theory. The assumption that an infinite sequence of data points is exchangeable is at the core of Bayesian statistics.
Broeck, Guy Van den, Niepert, Mathias
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Adaptive User Interfaces and the Use of Inference Methods
Computational Science and Techniques, 2021 Bayesian Networks are used to model a user's behaviour. There is not much research on the use of Frequentist Inference to accomplish this same task.
Rachelle Barrette, Ratvinder Grewal
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Conditional Inference in Small Sample Scenarios Using a Resampling Approach
Stats, 2021 This paper discusses a non-parametric resampling technique in the context of multidimensional or multiparameter hypothesis testing of assumptions of the Rasch model.
Clemens Draxler, Andreas Kurz
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