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Bayesian Inference

4821 directly classified papers

Papers per year

Papers

Tomography of the London Underground: a Scalable Model for Origin-Destination Data NIPS 2017
Perturbative Black Box Variational Inference NIPS 2017
Collapsed variational Bayes for Markov jump processes NIPS 2017
Scalable Variational Inference for Dynamical Systems NIPS 2017
Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference NIPS 2017
Overcoming Catastrophic Forgetting by Incremental Moment Matching NIPS 2017
Variational Inference for Gaussian Process Models with Linear Complexity NIPS 2017
Learning Kernels over Strings using Gaussian Processes IJCNLP 2017
Distributional Modeling on a Diet: One-shot Word Learning from Text Only IJCNLP 2017
A Bayesian Mixed-Effects Model to Learn Trajectories of Changes from Repeated Manifold-Valued Observations JMLR 2017
Hierarchically-partitioned Gaussian Process Approximation AISTATS 2017
Multi-fidelity Bayesian Optimisation with Continuous Approximations ICML 2017
Multi-way Interacting Regression via Factorization Machines NIPS 2017
Filtering Variational Objectives NIPS 2017
Convergence rates of a partition based Bayesian multivariate density estimation method NIPS 2017
Learning the Network Structure of Heterogeneous Data via Pairwise Exponential Markov Random Fields AISTATS 2017
Relativistic Monte Carlo AISTATS 2017
Black-box Importance Sampling AISTATS 2017
Scalable Bayesian Rule Lists ICML 2017
Variational Inference for Sparse and Undirected Models ICML 2017
Deep Generative Models for Relational Data with Side Information ICML 2017
A Divergence Bound for Hybrids of MCMC and Variational Inference and an Application to Langevin Dynamics and SGVI ICML 2017
Random Feature Expansions for Deep Gaussian Processes ICML 2017
Information-theoretic limits of Bayesian network structure learning AISTATS 2017
From Bayesian Sparsity to Gated Recurrent Nets NIPS 2017