• Suche: "Probabilistic programming"

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1

Semantics of Probabilistic Programs Using s-Finite Kernels in Dependent Type Theory
Affeldt, Reynald ; Cohen, Cyril ; Saito, Ayumu ; et al.
ACM Transactions on Probabilistic Machine Learning. 1(3):1-34

Rocq Probabilistic algorithms Denotational semantics Program verification formal proofs probabilistic programmin... …
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2

Introduction to probabilistic programming
Introduction à la programmation probabiliste
Baudart, Guillaume ; Tasson, Christine ; Les assistants à la démonstration au cœur du raisonnement mathématique (PICUBE) ; et al.
Benoît Delahaye. :117-156

semantics bayesian inference probabilistic programmin... [INFO.INFO-PL]Computer S... Programming Languages [c... [INFO.INFO-LG]Computer S... …
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3

Parallelizable Feynman-Kac Models for Universal Probabilistic Programming
Boreale M. ; Collodi L.
Electronic Proceedings in Theoretical Computer Science. 428:91-110

FOS: Computer and inform... operational semantics Probabilistic programmin... SIMD parallelism SMC Programming Languages …
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4

Applying Gaussian Process Machine Learning and Modern Probabilistic Programming to Satellite Data to Infer CO2 Emissions
Jeong, Seongeun ; Hamilton, Sofia D. ; Johnson, Matthew S. ; et al.
Environmental Science & Technology. 59(9):4376-4387

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5

Relaxations for probabilistically constrained stochastic programming problems: review and extensions
Lejeune, Miguel A. ; Prékopa, A.
Annals of Operations Research. 354(3):1227-1248

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6

Generalized Confidence Constraints
Perez, Guillaume ; Malalel, Steve ; Glorian, Gael ; et al.
The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23). :4078-4086

Washignton DC, United St... Constraint Programming Constraint Optimization Constraint Satisfaction Mixed Discrete Continuous Optimization …
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7

Evolutionary Synthesis of Probabilistic Programs
Romina Doz ; Francesca Randone ; Eric Medvet ; et al.
Proceedings of the Genetic and Evolutionary Computation Conference. :999-1007

Grammatical Evolution Ge...
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8

Variable Elimination as Rewriting in a Linear Lambda Calculus
Ehrhard, Thomas ; Faggian, Claudia ; Pagani, Michele ; et al.
Programming Languages and Systems - 34th European Symposium on Programming. :292-321

Hamilton, Canada Linear Logic Lambda Calculus Bayesian Inference Probabilistic Programmin... Denotational Semantics …
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9

Bayesian NVH metamodels to assess interior cabin noise using measurement databases
Métamodèles bayésiens NVH pour évaluer le bruit intérieur de la cabine à l'aide de bases de données de mesure
Prakash, V ; Sauvage, O ; Antoni, Jérôme ; et al.
International Conference on Noise and Vibration Engineering (ISMA). :1666-1682

Leuven (Louvain), KU Leu... Uncertainty quantificati... Automotive NVH Bayesian metamodel Probabilistic programmin... [SPI]Engineering Science... …
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10

Integration in Cones
Ehrhard, Thomas ; Geoffroy, Guillaume ; Institut de Recherche en Informatique Fondamentale (IRIF (UMR_8243)) ; et al.
Logical Methods in Computer Science, 2025, 21 (1)

Positive cones Linear logic Denotational semantics Probabilistic programmin... Integration Measurable spaces …
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11

Mixed Nondeterministic-Probabilistic Automata
Mixed Nondeterministic-Probabilistic Automata: Blending graphical probabilistic models with nondeterminism
Benveniste, Albert ; Raclet, Jean-Baptiste ; Modélisation hybride & conception par contrats pour les systèmes embarqués multi-physiques (HYCOMES) ; et al.
Discrete Event Dynamic Systems. 33(4):455-505

factor graphs nondeterminism and proba... probabilistic programmin... Bayesian networks semantics probabilistic automata …
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12

Automated Expected Value Analysis of Recursive Programs
Avanzini, Martin ; Moser, Georg ; Schaper, Michael ; et al.
Proceedings of the ACM on Programming Languages. :1050-1072

automation weakest pre-expectation... expected value analysis probabilistic programmin... [SCCO.COMP]Cognitive sci... Computer science
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13

A Bayesian regression framework for fault diagnosis in wind turbines
Chati, Yashovardhan S. ; Padullaparthi, Venkata Ramakrishna ; Vasan, Arunchandar
Discover Data. 3(1)

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14

Compiling Stan to generative probabilistic languages and extension to deep probabilistic programming
Baudart, Guillaume ; Burroni, Javier ; Hirzel, Martin ; et al.
PLDI '21 - 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation. :497-510

Virtual, Canada Pyro Stan Semantics Theory of computation →... Software and its enginee... …
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15

Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference
Lee, Wonyeol ; Rival, Xavier ; Yang, Hongseok ; et al.
Proceedings of the ACM on Programming Languages. 7:335-366

Variational inference Probabilistic programmin... Static analysis Smoothness [INFO]Computer Science [...
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16

Quantifying Privacy Risk with Gaussian Mixtures
Rønneberg, Rasmus C. ; Randone, Francesca ; Pardo, Raúl ; et al.
Software and Systems Modeling. :1-22

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17

Semi-symbolic inference for efficient streaming probabilistic programming
Atkinson, Eric ; Yuan, Charles ; Baudart, Guillaume ; et al.
Proceedings of the ACM on Programming Languages. 6:1668-1696

Probabilistic programmin... Streaming inference [INFO.INFO-ES]Computer S... Embedded Systems [INFO.INFO-PL]Computer S... Programming Languages [c... …
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18

Cones as a model of intuitionistic linear logic
Ehrhard, Thomas ; Institut de Recherche en Informatique Fondamentale (IRIF (UMR_8243)) ; Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS) ; et al.
LICS '20: 35th Annual ACM/IEEE Symposium on Logic in Computer Science. :370-383

Saarbrücken Germany, Ger... CCS Concepts: • Theory o... Categorical semantics De... probabilistic programmin... linear logic Denotational semantics …
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19

Inference Plans for Hybrid Particle Filtering
Ellie Y. Cheng ; Eric Atkinson ; Guillaume Baudart ; et al.
Proceedings of the ACM on Programming Languages. 9:271-299

FOS: Computer and inform... Computer Science - Progr... Artificial Intelligence... Probabilistic programmin... Computer Science - Artif... Abstract interpretation …
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20

Modelling Recursion and Probabilistic Choice in Guarded Type Theory
Philipp Stassen ; Rasmus Ejlers Møgelberg ; Maaike Annebet Zwart ; et al.
Stassen, P, Møgelberg, R E, Zwart, M A, Aguirre, A & Birkedal, L 2025, 'Modelling Recursion and Probabilistic Choice in Guarded Type Theory', Proceedings of the ACM on Programming Languages, vol. 9, no. POPL, 48, pp. 1417-1445. https://doi.org/10.1145/3704884

Probabilistic Programmin... FOS: Computer and inform... Computer Science - Logic... Computer Science - Progr... Type Theory F.3.2 …
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