hamiltonian monte carlo

Hamiltonian Variational Auto-Encoder NeurIPS 2018 Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning NeurIPS 2018 Turing: A Language for Flexible Probabilistic Inference AISTATS 2018 Underdamped Langevin MCMC: A non-asymptotic analysis COLT 2018 Adaptive Bayesian Sampling with Monte Carlo EM NeurIPS 2017 Asymptotically exact inference in differentiable generative models AISTATS 2017 Magnetic Hamiltonian Monte Carlo ICML 2017 Probabilistic Path Hamiltonian Monte Carlo ICML 2017 Relativistic Monte Carlo AISTATS 2017 Bayesian Optimization with Robust Bayesian Neural Networks NeurIPS 2016 Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo AISTATS 2016 Slice Sampling on Hamiltonian Trajectories ICML 2016 Towards Unifying Hamiltonian Monte Carlo and Slice Sampling NeurIPS 2016 A Complete Recipe for Stochastic Gradient MCMC NeurIPS 2015 Exponential Integration for Hamiltonian Monte Carlo ICML 2015 Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families NeurIPS 2015 On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators NeurIPS 2015 Reflection, Refraction, and Hamiltonian Monte Carlo NeurIPS 2015 The Fundamental Incompatibility of Scalable Hamiltonian Monte Carlo and Naive Data Subsampling ICML 2015 Bayesian Sampling Using Stochastic Gradient Thermostats NeurIPS 2014 Hamiltonian Monte Carlo Without Detailed Balance ICML 2014 Learning Generative Models with Visual Attention NeurIPS 2014 Positive Curvature and Hamiltonian Monte Carlo NeurIPS 2014 Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical Models NeurIPS 2014 Stochastic Gradient Hamiltonian Monte Carlo ICML 2014