Bayesian & Probabilistic

Interacting Contour Stochastic Gradient Langevin Dynamics ICLR 2022 Interpolating between sampling and variational inference with infinite stochastic mixtures UAI 2022 Interpreting Time-Varying Dynamic Bayesian Networks for Earth Climate Modelling PGM 2022 Iterative Structural Inference of Directed Graphs NeurIPS 2022 Joint Estimation of Direction-of-Arrival and Distance for Arrays with Directional Sensors based on Sparse Bayesian Learning Interspeech 2022 Jump Gaussian Process Model for Estimating Piecewise Continuous Regression Functions JMLR 2022 Kernel Interpolation with Sparse Grids NeurIPS 2022 Knowledge Distillation via Constrained Variational Inference AAAI 2022 Knowledge transfer for learning subject-specific causal models PGM 2022 Language modeling via stochastic processes ICLR 2022 Laplace Approximation Based Epistemic Uncertainty Estimation in 3D Object Detection CoRL 2022 Latent Time Neural Ordinary Differential Equations AAAI 2022 Learning explainable templated graphical models UAI 2022 Learning Expressive Meta-Representations with Mixture of Expert Neural Processes NeurIPS 2022 Learning from Stochastically Revealed Preference NeurIPS 2022 Learning Inconsistent Preferences with Gaussian Processes AISTATS 2022 Learning interacting dynamical systems with latent Gaussian process ODEs NeurIPS 2022 Learning large Bayesian networks with expert constraints UAI 2022 Learning Noisy-Or Networks with an Application in Linguistics PGM 2022 Learning Not to Learn: Nature versus Nurture In Silico AAAI 2022 Learning Object-Oriented Dynamics for Planning from Text ICLR 2022 Learning Optimal Flows for Non-Equilibrium Importance Sampling NeurIPS 2022 Learning POMDP Models with Similarity Space Regularization: a Linear Gaussian Case Study L4DC 2022 Learning Soft Estimator of Keypoint Scale and Orientation With Probabilistic Covariant Loss CVPR 2022 Learning Structured Gaussians To Approximate Deep Ensembles CVPR 2022