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Bayesian Inference

4821 directly classified papers

Papers per year

Papers

Getting More by Knowing Less: Bayesian Incentive Compatible Mechanisms for Fair Division IJCAI 2024
Probabilistic ODE solvers for integration error-aware numerical optimal control L4DC 2024
Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space COLT 2024
Parallel-in-Time Probabilistic Numerical ODE Solvers JMLR 2024
Modeling Random Networks with Heterogeneous Reciprocity JMLR 2024
Fixing Overconfidence in Dynamic Neural Networks WACV 2024
Lagrangian inspired polynomial estimator for black-box learning and control of underactuated systems L4DC 2024
Are you sure? Analysing Uncertainty Quantification Approaches for Real-world Speech Emotion Recognition INTERSPEECH 2024
Tensor-train methods for sequential state and parameter learning in state-space models JMLR 2024
A Framework for Improving the Reliability of Black-box Variational Inference JMLR 2024
Uncertainty Estimation in Instance Segmentation With Star-Convex Shapes WACV 2024
Physically consistent modeling & identification of nonlinear friction with dissipative Gaussian processes L4DC 2024
Efficient Hyperparameter Optimization with Adaptive Fidelity Identification CVPR 2024
A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression JMLR 2024
Uncertainty informed optimal resource allocation with Gaussian process based Bayesian inference L4DC 2024
Identifiable Feature Learning for Spatial Data with Nonlinear ICA AISTATS 2024
QCS-SGM+: Improved Quantized Compressed Sensing with Score-Based Generative Models AAAI 2024
Event-triggered safe Bayesian optimization on quadcopters L4DC 2024
Physics-constrained learning of PDE systems with uncertainty quantified port-Hamiltonian models L4DC 2024
An Analytic Solution to Covariance Propagation in Neural Networks AISTATS 2024
Watch Your Head: Assembling Projection Heads to Save the Reliability of Federated Models AAAI 2024
Accurate Training Data for Occupancy Map Prediction in Automated Driving Using Evidence Theory CVPR 2024
Variational Estimators of the Degree-corrected Latent Block Model for Bipartite Networks JMLR 2024
Nonstationary Sparse Spectral Permanental Process NIPS 2024
Evidence Estimation in Gaussian Graphical Models Using a Telescoping Block Decomposition of the Precision Matrix JMLR 2024