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Bayesian Inference

4,821 papers

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Papers

Wide Neural Networks with Bottlenecks are Deep Gaussian Processes JMLR 2020
Variational Inference for Computational Imaging Inverse Problems JMLR 2020
Contextual Explanation Networks JMLR 2020
Continuous-Time Birth-Death MCMC for Bayesian Regression Tree Models JMLR 2020
Efficient Inference for Nonparametric Hawkes Processes Using Auxiliary Latent Variables JMLR 2020
Structured Variational Inference in Partially Observable Unstable Gaussian Process State Space Models L4DC 2020
Regret Bound for Safe Gaussian Process Bandit Optimization L4DC 2020
Planning from Images with Deep Latent Gaussian Process Dynamics L4DC 2020
Uncertainty-Aware Training of Neural Networks for Selective Medical Image Segmentation MIDL 2020
Well-Calibrated Regression Uncertainty in Medical Imaging with Deep Learning MIDL 2020
Bayesian Learning of Probabilistic Dipole Inversion for Quantitative Susceptibility Mapping MIDL 2020
Comparisons Between Hamiltonian Monte Carlo and Maximum A Posteriori For A Bayesian Model For Apixaban Induction Dose & Dose Personalization MLHC 2020
Structure Learning from Related Data Sets with a Hierarchical Bayesian Score PGM 2020
Identifiability and Consistency of Bayesian Network Structure Learning from Incomplete Data PGM 2020
A Smooth Representation of Belief over SO(3) for Deep Rotation Learning with Uncertainty RSS 2020
Multi-Fidelity Black-Box Optimization for Time-Optimal Quadrotor Maneuvers RSS 2020
Active Preference-Based Gaussian Process Regression for Reward Learning RSS 2020
A Bayesian Framework for Nash Equilibrium Inference in Human-Robot Parallel Play RSS 2020
MRFMap: Online Probabilistic 3D Mapping using Forward Ray Sensor Models RSS 2020
Learning of Sub-optimal Gait Controllers for Magnetic Walking Soft Millirobots RSS 2020
Efficient Rollout Strategies for Bayesian Optimization UAI 2020
Compositional uncertainty in deep Gaussian processes UAI 2020
The Indian Chefs Process UAI 2020
Slice Sampling for General Completely Random Measures UAI 2020
Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks UAI 2020