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Papers matching “Bayesian inference” 36

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Fast and robust Bayesian Inference using Gaussian Processes with GPry
2022 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Jonas El Gammal, Nils Schöneberg, Jesús Torrado, Christian Fidler

1

citations
Exact Bayesian Inference for Loopy Probabilistic Programs using Generating Functions
2023 arXiv (Cornell University) preprint Computer Science Logic, programming, and type systems Open access

Lutz Klinkenberg, Mingshuai Chen

1

citations
Bayesian Inference in Quantum Programs
2025 arXiv (Cornell University) preprint Computer Science Logic, programming, and type systems Open access

Christina Gehnen, Dominique Unruh, Joost-Pieter Katoen

0

citations
Efficient Inference in Bayesian Networks with Continuous Variables A Discretization and Knowledge Compilation Approach
2023 SSRN Electronic Journal preprint Computer Science Bayesian Modeling and Causal Inference Open access

Maarten Vonk, Sebastiaan Brand, Ninoslav Malekovic, Thomas Bäck, Alfons Laarman, Anna V. Kononova

2

citations
A theory of data variability in Neural Network Bayesian inference
2023 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Javed Lindner, David Dahmen, Michael Krämer, Moritz Helias

0

citations
Discovering uncertainty: Bayesian constitutive artificial neural networks
2024 bioRxiv (Cold Spring Harbor Laboratory) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Kevin Linka, Gerhard A. Holzapfel, Ellen Kuhl

6

citations
How Does Bayesian Causal Discovery Fail? Characterising Structural Consequences in Linear Gaussian Networks under Latent Confounding
2026 arXiv (Cornell University) preprint Computer Science Bayesian Modeling and Causal Inference Open access

Debargha Ghosh, Silja Renooij, Anna Kononova

0

citations
Exact Inference for Continuous-Time Gaussian Process Dynamics
2023 RWTH Publications (RWTH Aachen) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Katharina Ensinger, Nicholas Tagliapietra, Sebastian Ziesche, Sebastian Trimpe

0

citations
Disentangling causality: assumptions in causal discovery and inference
2022 Research Square preprint Computer Science Bayesian Modeling and Causal Inference Open access

Maarten Vonk, Ninoslav Malekovic, Thomas Bäck, Anna V. Kononova

7

citations
Bayesian calibration, process modeling and uncertainty quantification in biotechnology
2021 bioRxiv (Cold Spring Harbor Laboratory) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Laura M. Helleckes, Michael Osthege, Wolfgang Wiechert, Eric von Lieres, Marco Oldiges

4

citations
Bayesian Optimization via Continual Variational Last Layer Training
2024 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Paul Brunzema, Mikkel Jordahn, John Willes, Sebastian Trimpe, Jasper Snoek

0

citations
Optimizing Causal Interventions in Hybrid Bayesian Networks
2024 Research Square preprint Computer Science Bayesian Modeling and Causal Inference Open access

Maarten Vonk, Diederick Vermetten, Jacob de Nobel, Sebastiaan Brand, Ninoslav Malekovic, Thomas Bäck, +2 more

0

citations
Meta-Learning Conjugate Priors for Few-Shot Bayesian Optimization
2021 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Ruduan Benjamin Franklin Plug

0

citations
Finding an $ε$-close Variation of Parameters in Bayesian Networks
2023 arXiv (Cornell University) preprint Computer Science Bayesian Modeling and Causal Inference Open access

Bahare Salmani, Joost-Pieter Katoen

0

citations
Parameter-efficient Bayesian Neural Networks for Uncertainty-aware Depth Estimation
2024 arXiv (Cornell University) preprint Computer Science Advanced Neural Network Applications Open access

Richard D. Paul, Alessio Quercia, Vincent Fortuin, Katharina Nöh, Hanno Scharr

0

citations
Bayesian Optimization of Partially Known Systems using Hybrid Models
2026 arXiv (Cornell University) preprint Computer Science Advanced Multi-Objective Optimization Algorithms Open access

Eike Cramer, Luis Kutschat, Oliver Stollenwerk, Joel A. Paulson, Alexander Mitsos

0

citations
Scalable Gaussian Process Regression via Deterministic Trigonometric Features: Uniform Bounds for Safe Model Predictive Control
2026 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Julius Jagdt, Johanna Menn, Sebastian Trimpe, Melanie N. Zeilinger, Anna Scampicchio

0

citations
Integrated Multimodal Data Pipelines for Intelligent Security Monitoring in Smart Cities
2025 Preprints.org preprint Computer Science Video Surveillance and Tracking Methods Open access

Johannes Richter, Felix K. Wagner

0

citations
ACTIVA: Amortized Causal Effect Estimation via Transformer-based Variational Autoencoder
2025 arXiv (Cornell University) preprint Computer Science Bayesian Modeling and Causal Inference Open access

Saber Salehkaleybar, Aske Plaat, Erman Acar

0

citations
Critical feature learning in deep neural networks
2024 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Javed Lindner, David Dahmen, Zohar Ringel, M. Krämer, Moritz Helias

0

citations
Probabilistic Robust Linear Quadratic Regulators with Gaussian Processes
2021 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Alexander von Rohr, Matthias Neumann-Brosig, Sebastian Trimpe

10

citations
Data-Driven Covariate Selection for Nonparametric and Cycle-Agnostic Causal Effect Estimation
2026 arXiv (Cornell University) preprint Computer Science Bayesian Modeling and Causal Inference Open access

Ana Letícia Garcez Vicente, Gijs van Seeventer, Saber Salehkaleybar

0

citations
Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues
2026 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Jakob Kramp, Javed Lindner, Moritz Helias

0

citations
Optimal recovery and uncertainty quantification for distributed Gaussian process regression
2022 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Amine Hadji, Tammo Hesselink, Botond Szabó

3

citations
Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression
2021 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Christian Fiedler, Carsten W. Scherer, Sebastian Trimpe

9

citations