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Compositionality Meets Belief Revision: a Bayesian Model of Modification

Corina Strößner
2020 Review of Philosophy and Psychology  
Moreover, we relate this model to systems of defeasible reasoning as discussed in the field of artificial intelligence.  ...  I am grateful to my project colleagues Annika Schuster, Gerhard Schurz and Paul Thorn as well as Peter Sutton and Henk Zeevat with whom I discussed probabilistic versions of frames while working on this  ...  Apart from that, we generally defend a default inheritance strategy: if no constraint is involved, values are inherited.  ... 
doi:10.1007/s13164-020-00476-8 fatcat:xelt6mc5obdcpgcu7wb7tjkhla

Probabilistic Causal Reasoning [article]

Thomas L. Dean, Keiji Kanazawa
2013 arXiv   pre-print
We emphasize a common type of prediction that involves reasoning about persistence: whether or not a proposition once made true remains true at some later time.  ...  In this paper, we develop a theory of causal reasoning for predictive inference under uncertainty.  ...  Probabilistic projection is a special case of reasoning about contin uously changing quantities involving partial orders and other sorts of �ncomplete information, and as such it represents an intractable  ... 
arXiv:1304.2348v1 fatcat:bb5nrjfa6jhnbkeqzwsvuvkcri

Model-Based Probabilistic Reasoning for Self-Diagnosis of Telecommunication Networks: Application to a GPON-FTTH Access Network

S. R. Tembo, S. Vaton, J. L. Courant, S. Gosselin, M. Beuvelot
2016 Journal of Network and Systems Management  
Model-based probabilistic reasoning for self-diagnosis of telecommunication networks: application to a GPON-FTTH access network.  ...  Obtained self-diagnosis results are very satisfying and we show how and why these results of the probabilistic model are more consistent with 1 the behaviour of the GPON-FTTH network, and more reasonable  ...  We also plan to refine and upgrade the probabilistic model in order to consider GPON network evolutions like xGPON, NG-PON (Next Generation PON) and NG-PON-2.  ... 
doi:10.1007/s10922-016-9401-0 fatcat:s6cnvyryibgpdjsxtpaavg2awi

Comparative Evaluation of Predictive Modeling Techniques on Credit Card Data

Ravinder Singh, Rinkle Rani Aggarwal
2011 Journal of clean energy technologies  
Kernel Discrimination A common approach to non parametric discriminant analysis with continous or discrete nature of predictor variables is to substitute non parametric estimates of group conditional densities  ...  A new set is generated by probabilistically selecting the fit individuals from the current population.  ... 
doi:10.7763/ijcte.2011.v3.377 fatcat:nc4lmm7zhjexto2hd4pqahil2m

Using Semantics and Statistics to Turn Data into Knowledge

Jay Pujara, Hui Miao, Lise Getoor, William W. Cohen
2015 The AI Magazine  
Knowledge graph identification requires reasoning jointly over millions of extractions simultaneously, posing a scalability challenge to many approaches.  ...  We use probabilistic soft logic (PSL), a recently-introduced statistical relational learning framework, to implement an efficient solution to knowledge graph identification and present state-of-the-art  ...  continent.  ... 
doi:10.1609/aimag.v36i1.2568 fatcat:2qovmvqojvaibalbnqsrirx4xq

AIRCC-Clim: a user-friendly tool for generating regional probabilistic climate change scenarios and risk measures [article]

Francisco Estrada, Oscar Calderón-Bustamante, Wouter Botzen, Julián A. Velasco, Richard S.J. Tol
2021 arXiv   pre-print
Here we present AIRCC-Clim, a simple climate model emulator that produces regional probabilistic climate change projections of monthly and annual temperature and precipitation, as well as risk measures  ...  The default value in AIRCC-Clim is 50%.  ...  These techniques produce adequate approximations for variables such as annual/seasonal temperature and precipitation and other variables excluding extreme events and time-scales in which natural variability  ... 
arXiv:2111.01762v1 fatcat:uciufrs7argnnow27b7myoj73y

Learning Directed Relational Models with Recursive Dependencies [chapter]

Oliver Schulte, Hassan Khosravi, Tong Man
2012 Lecture Notes in Computer Science  
Recently, there has been an increasing interest in generative models that represent probabilistic patterns over both links and attributes.  ...  We propose a new normal form format that removes the redundancy, and prove that assuming stratification, the normal form constraints involve no loss of modelling power.  ...  This assumption does not involve a loss of modelling power because a functor node with a repeated variable can be rewritten using a new functor symbol (provided the functor node contains at least one variable  ... 
doi:10.1007/978-3-642-31951-8_8 fatcat:iyjjjygeeba2ndlzjuqrc3m5dq

Learning directed relational models with recursive dependencies

Oliver Schulte, Hassan Khosravi, Tong Man
2012 Machine Learning  
Recently, there has been an increasing interest in generative models that represent probabilistic patterns over both links and attributes.  ...  We propose a new normal form format that removes the redundancy, and prove that assuming stratification, the normal form constraints involve no loss of modelling power.  ...  This assumption does not involve a loss of modelling power because a functor node with a repeated variable can be rewritten using a new functor symbol (provided the functor node contains at least one variable  ... 
doi:10.1007/s10994-012-5308-5 fatcat:hjo6n4dnlbh55oomtzgyeumqzq

Stepping out: a computer simulation of hominid dispersal from Africa

Steven Mithen, Melissa Reed
2002 Journal of Human Evolution  
We use this when exploring possible reasons for a relatively late colonization of Europe.  ...  Each simulation involves 30 runs with the same parameter values.  ... 
doi:10.1006/jhev.2002.0584 pmid:12393003 fatcat:vjmutpqgubevrobaqeiml4et34

Stepping out: a computer simulation of hominid dispersal from Africa

S Mithen
2002 Journal of Human Evolution  
We use this when exploring possible reasons for a relatively late colonization of Europe.  ...  Each simulation involves 30 runs with the same parameter values.  ... 
doi:10.1016/s0047-2484(02)90584-1 pmid:12393003 fatcat:scfuyvlxfzfdrhgfezhzvmmnom

The First Probabilistic Track of the International Planning Competition

H.L.S. Younes, M. L. Littman, D. Weissman, J. Asmuth
2005 The Journal of Artificial Intelligence Research  
The 2004 International Planning Competition, IPC-4, included a probabilistic planning track for the first time.  ...  We made this decision for two reasons: The first is that parsing the messages into an easily managed format was trivial for all parties involved-many solid XML parsers exist in the public domain.  ...  There are three auxiliary variables because the action effect contains three probabilistic effects.  ... 
doi:10.1613/jair.1880 fatcat:q4uc4glzqngdtpwxfl2slmdcp4

Knowledge Based Bayesian Network Construction Algorithm for Medical Data Fusion to Enhance Services and Diagnosis

Ahmed Sameh
2019 Journal of Computer Science  
It demonstrates learning of probabilities, network structure and mixes discrete and continuous variables.  ...  It also extracts Bayesian data variables from the "King Abdullah Encyclopedia" server to aid in constructing and learning the ontology-based Bayesian networks.  ...  Both continous and discrete variables are handled following standard Bayesian rules. Data are divided into both training and verification data.  ... 
doi:10.3844/jcssp.2019.612.634 fatcat:mhe43nm3dvfafbhqou3v67fqie

PODS

Thanh T.L. Tran, Liping Peng, Boduo Li, Yanlei Diao, Anna Liu
2010 Proceedings of the 2010 international conference on Management of data - SIGMOD '10  
In this paper, we present the PODS system that supports stream processing for uncertain data naturally captured using continuous random variables.  ...  To attain proper result distributions for equijoins involving continuous random variables, we introduce the notion of a probabilistic view.  ...  These issues are inherent in equijoins involving continuous random variables.  ... 
doi:10.1145/1807167.1807187 dblp:conf/sigmod/TranPLDL10 fatcat:pfonw4lck5hrlmu5n7tam4mgny

Event Recognition for Unobtrusive Assisted Living [chapter]

Nikos Katzouris, Alexander Artikis, Georgios Paliouras
2014 Lecture Notes in Computer Science  
In particular, we present our knowledge-driven approach to the detection of Activities of Daily Living (ADL) and functional ability, based on a probabilistic version of the Event Calculus.  ...  Probabilistic facts in ProbLog represent random variables with an independence assumption, thus a rule defined as a conjunction of a set of probabilistic facts, has a probability that is equal to the product  ...  [15] does not support probabilistic reasoning and relies on (crisp) ASP constructs in order to address uncertainty.  ... 
doi:10.1007/978-3-319-07064-3_41 fatcat:imszu6qqzbdp5he3hav6mdtx4e

Machine learning-based integration of large-scale climate drivers can improve the forecast of seasonal rainfall probability in Australia

Puyu Feng, Bin Wang, De Li (Deli) Liu, Fei Ji, Xiaoli Niu, Hongyan Ruan, Lijie Shi, Qiang Yu
2020 Environmental Research Letters  
For these reasons, we conducted a case study in Australia by developing a machine learning-based probabilistic seasonal rainfall forecasting model using multiple large-scale climate indices from the Pacific  ...  Statistical models are easy to implement but are usually based on simple or linear relationships between observed variables.  ...  Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request.  ... 
doi:10.1088/1748-9326/ab9e98 fatcat:a5s3wpfdg5f4znhsazdfaezruy
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