Artykuły w czasopismach na temat „Exact and approximate inferences”
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Wu, Lang. "Exact and Approximate Inferences for Nonlinear Mixed-Effects Models With Missing Covariates". Journal of the American Statistical Association 99, nr 467 (wrzesień 2004): 700–709. http://dx.doi.org/10.1198/016214504000001006.
Pełny tekst źródłaMekhnacha, Kamel, Juan-Manuel Ahuactzin, Pierre Bessière, Emmanuel Mazer i Linda Smail. "Exact and approximate inference in ProBT". Revue d'intelligence artificielle 21, nr 3 (12.06.2007): 295–332. http://dx.doi.org/10.3166/ria.21.295-332.
Pełny tekst źródłaAkagi, Yasunori, Takuya Nishimura, Yusuke Tanaka, Takeshi Kurashima i Hiroyuki Toda. "Exact and Efficient Inference for Collective Flow Diffusion Model via Minimum Convex Cost Flow Algorithm". Proceedings of the AAAI Conference on Artificial Intelligence 34, nr 04 (3.04.2020): 3163–70. http://dx.doi.org/10.1609/aaai.v34i04.5713.
Pełny tekst źródłaAbe, Takayuki, i Manabu Iwasaki. "EXACT AND APPROXIMATE INFERENCES FOR AN EXPONENTIAL MEAN FROM TYPE I CENSORED DATA". Bulletin of informatics and cybernetics 37 (grudzień 2005): 31–39. http://dx.doi.org/10.5109/12589.
Pełny tekst źródłaYANG, HANN-PYI JAMES, i WEI-KEI SHIUE. "COMPARISON OF FAILURE INTENSITIES FROM TWO POISSON PROCESSES". International Journal of Reliability, Quality and Safety Engineering 02, nr 03 (wrzesień 1995): 235–43. http://dx.doi.org/10.1142/s0218539395000186.
Pełny tekst źródłaKarami, Md Jamil Hasan. "Assessing Goodness of Approximate Distributions for Inferences about Parameters in Nonlinear Regression Model". Dhaka University Journal of Science 71, nr 1 (29.05.2023): 13–16. http://dx.doi.org/10.3329/dujs.v71i1.65267.
Pełny tekst źródłaEl-Sagheer, Rashad M., Taghreed M. Jawa i Neveen Sayed-Ahmed. "Inferences for Generalized Pareto Distribution Based on Progressive First-Failure Censoring Scheme". Complexity 2021 (7.12.2021): 1–11. http://dx.doi.org/10.1155/2021/9325928.
Pełny tekst źródłaLintusaari, Jarno, Paul Blomstedt, Tuomas Sivula, Michael U. Gutmann, Samuel Kaski i Jukka Corander. "Resolving outbreak dynamics using approximate Bayesian computation for stochastic birth-death models". Wellcome Open Research 4 (25.01.2019): 14. http://dx.doi.org/10.12688/wellcomeopenres.15048.1.
Pełny tekst źródłaLintusaari, Jarno, Paul Blomstedt, Brittany Rose, Tuomas Sivula, Michael U. Gutmann, Samuel Kaski i Jukka Corander. "Resolving outbreak dynamics using approximate Bayesian computation for stochastic birth–death models". Wellcome Open Research 4 (30.08.2019): 14. http://dx.doi.org/10.12688/wellcomeopenres.15048.2.
Pełny tekst źródłaShapovalova, Yuliya. "“Exact” and Approximate Methods for Bayesian Inference: Stochastic Volatility Case Study". Entropy 23, nr 4 (15.04.2021): 466. http://dx.doi.org/10.3390/e23040466.
Pełny tekst źródłaFioretto, Ferdinando, Enrico Pontelli, William Yeoh i Rina Dechter. "Accelerating exact and approximate inference for (distributed) discrete optimization with GPUs". Constraints 23, nr 1 (18.08.2017): 1–43. http://dx.doi.org/10.1007/s10601-017-9274-1.
Pełny tekst źródłaTarvirdizade, Bahman, i Hossein Kazemzadeh Garehchobogh. "Interval Estimation of Stress-Strength Reliability Based on Lower Record Values from Inverse Rayleigh Distribution". Journal of Quality and Reliability Engineering 2014 (16.11.2014): 1–8. http://dx.doi.org/10.1155/2014/192072.
Pełny tekst źródłaGuo, Yuanzhen, Hao Xiong i Nicholas Ruozzi. "Marginal Inference in Continuous Markov Random Fields Using Mixtures". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17.07.2019): 7834–41. http://dx.doi.org/10.1609/aaai.v33i01.33017834.
Pełny tekst źródłaKenig, Batya, i Benny Kimelfeld. "Approximate Inference of Outcomes in Probabilistic Elections". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17.07.2019): 2061–68. http://dx.doi.org/10.1609/aaai.v33i01.33012061.
Pełny tekst źródłaSeridi, Hamid, Herman Akdag, Rachid Mansouri i Mohamed Nemissi. "Approximate Reasoning in Supervised Classification Systems". Journal of Advanced Computational Intelligence and Intelligent Informatics 10, nr 4 (20.07.2006): 586–93. http://dx.doi.org/10.20965/jaciii.2006.p0586.
Pełny tekst źródłaTucci, Beatriz, i Fabian Schmidt. "EFTofLSS meets simulation-based inference: σ 8 from biased tracers". Journal of Cosmology and Astroparticle Physics 2024, nr 05 (1.05.2024): 063. http://dx.doi.org/10.1088/1475-7516/2024/05/063.
Pełny tekst źródłaDomínguez, E., i H. J. Kappen. "Efficient inference in the transverse field Ising model". Journal of Statistical Mechanics: Theory and Experiment 2023, nr 3 (1.03.2023): 033301. http://dx.doi.org/10.1088/1742-5468/acba02.
Pełny tekst źródłaAtkinson, Eric, Charles Yuan, Guillaume Baudart, Louis Mandel i Michael Carbin. "Semi-symbolic inference for efficient streaming probabilistic programming". Proceedings of the ACM on Programming Languages 6, OOPSLA2 (31.10.2022): 1668–96. http://dx.doi.org/10.1145/3563347.
Pełny tekst źródłaDemidenko, Eugene. "Exact and Approximate Statistical Inference for Nonlinear Regression and the Estimating Equation Approach". Scandinavian Journal of Statistics 44, nr 3 (29.03.2017): 636–65. http://dx.doi.org/10.1111/sjos.12269.
Pełny tekst źródłaÇakmak, Burak, Yue M. Lu i Manfred Opper. "Analysis of random sequential message passing algorithms for approximate inference". Journal of Statistical Mechanics: Theory and Experiment 2022, nr 7 (1.07.2022): 073401. http://dx.doi.org/10.1088/1742-5468/ac764a.
Pełny tekst źródłaRandone, Francesca, Luca Bortolussi, Emilio Incerto i Mirco Tribastone. "Inference of Probabilistic Programs with Moment-Matching Gaussian Mixtures". Proceedings of the ACM on Programming Languages 8, POPL (5.01.2024): 1882–912. http://dx.doi.org/10.1145/3632905.
Pełny tekst źródłaDe Santis, Fulvio, i Stefania Gubbiotti. "Sample Size Requirements for Calibrated Approximate Credible Intervals for Proportions in Clinical Trials". International Journal of Environmental Research and Public Health 18, nr 2 (12.01.2021): 595. http://dx.doi.org/10.3390/ijerph18020595.
Pełny tekst źródłaCANO, ANDRÉS, MANUEL GÓMEZ-OLMEDO, CORA B. PÉREZ-ARIZA i ANTONIO SALMERÓN. "FAST FACTORISATION OF PROBABILISTIC POTENTIALS AND ITS APPLICATION TO APPROXIMATE INFERENCE IN BAYESIAN NETWORKS". International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 20, nr 02 (kwiecień 2012): 223–43. http://dx.doi.org/10.1142/s0218488512500110.
Pełny tekst źródłaSchälte, Yannik, i Jan Hasenauer. "Efficient exact inference for dynamical systems with noisy measurements using sequential approximate Bayesian computation". Bioinformatics 36, Supplement_1 (1.07.2020): i551—i559. http://dx.doi.org/10.1093/bioinformatics/btaa397.
Pełny tekst źródłaDemidenko, Eugene, Benjamin B. Williams, Ann Barry Flood i Harold M. Swartz. "Standard error of inverse prediction for dose-response relationship: approximate and exact statistical inference". Statistics in Medicine 32, nr 12 (5.11.2012): 2048–61. http://dx.doi.org/10.1002/sim.5668.
Pełny tekst źródłaVan den Broek, B., W. Wiegerinck i B. Kappen. "Graphical Model Inference in Optimal Control of Stochastic Multi-Agent Systems". Journal of Artificial Intelligence Research 32 (16.05.2008): 95–122. http://dx.doi.org/10.1613/jair.2473.
Pełny tekst źródłaDaly, Aidan C., Jonathan Cooper, David J. Gavaghan i Chris Holmes. "Comparing two sequential Monte Carlo samplers for exact and approximate Bayesian inference on biological models". Journal of The Royal Society Interface 14, nr 134 (wrzesień 2017): 20170340. http://dx.doi.org/10.1098/rsif.2017.0340.
Pełny tekst źródłaCabañas, Rafael, Manuel Gómez-Olmedo i Andrés Cano. "Using Binary Trees for the Evaluation of Influence Diagrams". International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 24, nr 01 (luty 2016): 59–89. http://dx.doi.org/10.1142/s0218488516500045.
Pełny tekst źródłaNAMPALLY, ARUN, TIMOTHY ZHANG i C. R. RAMAKRISHNAN. "Constraint-Based Inference in Probabilistic Logic Programs". Theory and Practice of Logic Programming 18, nr 3-4 (lipiec 2018): 638–55. http://dx.doi.org/10.1017/s1471068418000273.
Pełny tekst źródłaEnsinger, Katharina, Nicholas Tagliapietra, Sebastian Ziesche i Sebastian Trimpe. "Exact Inference for Continuous-Time Gaussian Process Dynamics". Proceedings of the AAAI Conference on Artificial Intelligence 38, nr 11 (24.03.2024): 11883–91. http://dx.doi.org/10.1609/aaai.v38i11.29074.
Pełny tekst źródłaCano, Andrés, Manuel Gómez, Serafín Moral i Joaquín Abellán. "Hill-climbing and branch-and-bound algorithms for exact and approximate inference in credal networks". International Journal of Approximate Reasoning 44, nr 3 (marzec 2007): 261–80. http://dx.doi.org/10.1016/j.ijar.2006.07.020.
Pełny tekst źródłaDrovandi, Christopher C., Anthony N. Pettitt i Roy A. McCutchan. "Exact and Approximate Bayesian Inference for Low Integer-Valued Time Series Models with Intractable Likelihoods". Bayesian Analysis 11, nr 2 (czerwiec 2016): 325–52. http://dx.doi.org/10.1214/15-ba950.
Pełny tekst źródłaFeldman, A., G. Provan i A. Van Gemund. "Approximate Model-Based Diagnosis Using Greedy Stochastic Search". Journal of Artificial Intelligence Research 38 (27.07.2010): 371–413. http://dx.doi.org/10.1613/jair.3025.
Pełny tekst źródłaTaghipour, N., D. Fierens, J. Davis i H. Blockeel. "Lifted Variable Elimination: Decoupling the Operators from the Constraint Language". Journal of Artificial Intelligence Research 47 (8.07.2013): 393–439. http://dx.doi.org/10.1613/jair.3793.
Pełny tekst źródłavan Lieshout, M. N. M., i E. W. van Zwet. "Exact sampling from conditional Boolean models with applications to maximum likelihood inference". Advances in Applied Probability 33, nr 2 (czerwiec 2001): 339–53. http://dx.doi.org/10.1017/s000186780001082x.
Pełny tekst źródłaAlnosaier, Waseem. "Comparisons of the Satterthwaite Approaches for Fixed Effects in Linear Mixed Models". International Journal of Statistics and Probability 13, nr 1 (28.02.2024): 22. http://dx.doi.org/10.5539/ijsp.v13n1p22.
Pełny tekst źródłaMasegosa, Andrés R., Rafael Cabañas, Helge Langseth, Thomas D. Nielsen i Antonio Salmerón. "Probabilistic Models with Deep Neural Networks". Entropy 23, nr 1 (18.01.2021): 117. http://dx.doi.org/10.3390/e23010117.
Pełny tekst źródłaAlahmadi, Amani A., Jennifer A. Flegg, Davis G. Cochrane, Christopher C. Drovandi i Jonathan M. Keith. "A comparison of approximate versus exact techniques for Bayesian parameter inference in nonlinear ordinary differential equation models". Royal Society Open Science 7, nr 3 (marzec 2020): 191315. http://dx.doi.org/10.1098/rsos.191315.
Pełny tekst źródłaSeo, Jung-In, Jae-Woo Jeon i Suk-Bok Kang. "Exact Interval Inference for the Two-Parameter Rayleigh Distribution Based on the Upper Record Values". Journal of Probability and Statistics 2016 (2016): 1–5. http://dx.doi.org/10.1155/2016/8246390.
Pełny tekst źródłaVolaufová, Júlia, i Viktor Witkovský. "On exact inference in linear models with two variance-covariance components". Tatra Mountains Mathematical Publications 51, nr 1 (1.11.2012): 173–81. http://dx.doi.org/10.2478/v10127-012-0017-9.
Pełny tekst źródłaGHAHRAMANI, ZOUBIN. "AN INTRODUCTION TO HIDDEN MARKOV MODELS AND BAYESIAN NETWORKS". International Journal of Pattern Recognition and Artificial Intelligence 15, nr 01 (luty 2001): 9–42. http://dx.doi.org/10.1142/s0218001401000836.
Pełny tekst źródłaFriston, Karl J., Lancelot Da Costa i Thomas Parr. "Some Interesting Observations on the Free Energy Principle". Entropy 23, nr 8 (19.08.2021): 1076. http://dx.doi.org/10.3390/e23081076.
Pełny tekst źródłaUllah, Insha, Sudhir Paul, Zhenjie Hong i You-Gan Wang. "Significance tests for analyzing gene expression data with small sample sizes". Bioinformatics 35, nr 20 (15.03.2019): 3996–4003. http://dx.doi.org/10.1093/bioinformatics/btz189.
Pełny tekst źródłaHuang, Kai, i Jie Mi. "Inference about Weibull Distribution Using Upper Record Values". International Journal of Reliability, Quality and Safety Engineering 22, nr 04 (sierpień 2015): 1550016. http://dx.doi.org/10.1142/s0218539315500163.
Pełny tekst źródłaJaakkola, T. S., i M. I. Jordan. "Variational Probabilistic Inference and the QMR-DT Network". Journal of Artificial Intelligence Research 10 (1.05.1999): 291–322. http://dx.doi.org/10.1613/jair.583.
Pełny tekst źródłaJiao, Jiajia. "HEAP: A Holistic Error Assessment Framework for Multiple Approximations Using Probabilistic Graphical Models". Electronics 9, nr 2 (22.02.2020): 373. http://dx.doi.org/10.3390/electronics9020373.
Pełny tekst źródłaMiller, David J., i Lian Yan. "Approximate Maximum Entropy Joint Feature Inference Consistent with Arbitrary Lower-Order Probability Constraints: Application to Statistical Classification". Neural Computation 12, nr 9 (1.09.2000): 2175–207. http://dx.doi.org/10.1162/089976600300015105.
Pełny tekst źródłaLin, Peng, Martin Neil i Norman Fenton. "Improved High Dimensional Discrete Bayesian Network Inference using Triplet Region Construction". Journal of Artificial Intelligence Research 69 (27.09.2020): 231–95. http://dx.doi.org/10.1613/jair.1.12198.
Pełny tekst źródłaMozer, Reagan, Luke Miratrix, Aaron Russell Kaufman i L. Jason Anastasopoulos. "Matching with Text Data: An Experimental Evaluation of Methods for Matching Documents and of Measuring Match Quality". Political Analysis 28, nr 4 (17.03.2020): 445–68. http://dx.doi.org/10.1017/pan.2020.1.
Pełny tekst źródłaZhu, Jianping, Hua Xin, Chenlu Zheng i Tzong-Ru Tsai. "Inference for the Process Performance Index of Products on the Basis of Power-Normal Distribution". Mathematics 10, nr 1 (23.12.2021): 35. http://dx.doi.org/10.3390/math10010035.
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