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Bayesian Inference

4821 directly classified papers

Papers per year

Papers

To Believe or Not to Believe Your LLM: Iterative Prompting for Estimating Epistemic Uncertainty NIPS 2024
Safe Time-Varying Optimization based on Gaussian Processes with Spatio-Temporal Kernel NIPS 2024
On Unbiased Estimation for Partially Observed Diffusions JMLR 2024
MAPTree: Beating “Optimal” Decision Trees with Bayesian Decision Trees AAAI 2024
Optimal Design for Human Preference Elicitation NIPS 2024
Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal NIPS 2024
On Truthing Issues in Supervised Classification JMLR 2024
Robust Gaussian Processes via Relevance Pursuit NIPS 2024
Gated Inference Network: Inference and Learning State-Space Models NIPS 2024
Modeling Random Networks with Heterogeneous Reciprocity JMLR 2024
Bidirectional Recurrence for Cardiac Motion Tracking with Gaussian Process Latent Coding NIPS 2024
Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems NIPS 2024
Mean-Square Analysis of Discretized Itô Diffusions for Heavy-tailed Sampling JMLR 2024
Constrained Sampling with Primal-Dual Langevin Monte Carlo NIPS 2024
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes NIPS 2024
A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression JMLR 2024
Kernelized Normalizing Constant Estimation: Bridging Bayesian Quadrature and Bayesian Optimization AAAI 2024
Bayesian Domain Adaptation with Gaussian Mixture Domain-Indexing NIPS 2024
Boosting Vision-Language Models with Transduction NIPS 2024
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations NIPS 2024
Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction NIPS 2024
Hyper-opinion Evidential Deep Learning for Out-of-Distribution Detection NIPS 2024
Leveraging an ECG Beat Diffusion Model for Morphological Reconstruction from Indirect Signals NIPS 2024
Boundary constrained Gaussian processes for robust physics-informed machine learning of linear partial differential equations JMLR 2024
Amortizing intractable inference in diffusion models for vision, language, and control NIPS 2024