Bayesian & Probabilistic

Fixing the Bethe approximation: How structural modifications in a graph improve belief propagation UAI 2022 Flow-Adapter Architecture for Unsupervised Machine Translation ACL 2022 FlowHMM: Flow-based continuous hidden Markov models NeurIPS 2022 Forecasting Characteristic 3D Poses of Human Actions CVPR 2022 Forward-Backward Latent State Inference for Hidden Continuous-Time semi-Markov Chains NeurIPS 2022 Foundation Posteriors for Approximate Probabilistic Inference NeurIPS 2022 FuDGE: A Method to Estimate a Functional Differential Graph in a High-Dimensional Setting JMLR 2022 Functional Ensemble Distillation NeurIPS 2022 GammaE: Gamma Embeddings for Logical Queries on Knowledge Graphs EMNLP 2022 Gardner formula for Ising perceptron models at small densities COLT 2022 GATSBI: Generative Adversarial Training for Simulation-Based Inference ICLR 2022 Gaussian Copula Embeddings NeurIPS 2022 Gaussian Process Modeling of Approximate Inference Errors for Variational Autoencoders CVPR 2022 Gaussian Process Parameter Estimation Using Mini-batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits JMLR 2022 Gauss-Legendre Features for Gaussian Process Regression JMLR 2022 Generalised GPLVM with Stochastic Variational Inference AISTATS 2022 Generalized Bayesian quadrature with spectral kernels UAI 2022 Generalizing Bayesian Optimization with Decision-theoretic Entropies NeurIPS 2022 Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning NeurIPS 2022 Generative Flow Networks for Discrete Probabilistic Modeling ICML 2022 Geometry-Aware Hierarchical Bayesian Learning on Manifolds WACV 2022 GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models NeurIPS 2022 Group equivariant neural posterior estimation ICLR 2022 Hardness of Maximum Likelihood Learning of DPPs COLT 2022 Hedging as Reward Augmentation in Probabilistic Graphical Models NeurIPS 2022