monte carlo sampling

Nonparametric learning from Bayesian models with randomized objective functions NeurIPS 2018 On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo ICML 2018 Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation NeurIPS 2018 Optimizing Expected Word Error Rate via Sampling for Speech Recognition Interspeech 2017 Variational Inference for Sparse and Undirected Models ICML 2017 Robust Monte Carlo Sampling using Riemannian Nosé-Poincaré Hamiltonian Dynamics ICML 2016 Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling NeurIPS 2015 Fast Bidirectional Probability Estimation in Markov Models NeurIPS 2015 Multi-Conditional Latent Variable Model for Joint Facial Action Unit Detection ICCV 2015 Reflection, Refraction, and Hamiltonian Monte Carlo NeurIPS 2015 Black Box Variational Inference AISTATS 2014 Neurons as Monte Carlo Samplers: Bayesian Inference and Learning in Spiking Networks NeurIPS 2014 Annealing between distributions by averaging moments NeurIPS 2013 Dynamic Scaled Sampling for Deterministic Constraints AISTATS 2013 Flexible sampling of discrete data correlations without the marginal distributions NeurIPS 2013 Metastability for High-Dimensional Walking Systems on Stochastically Rough Terrain RSS 2013 Probabilistic Principal Geodesic Analysis NeurIPS 2013 Summary Statistics for Partitionings and Feature Allocations NeurIPS 2013 Efficient Monte Carlo Counterfactual Regret Minimization in Games with Many Player Actions NeurIPS 2012 Active Sequential Learning with Tactile Feedback AISTATS 2010 Monte-Carlo Planning in Large POMDPs NeurIPS 2010 An Ab-initio tree-based exploration to enhance sampling of low-energy protein conformations RSS 2009 Clustering sequence sets for motif discovery NeurIPS 2009 Monte Carlo Sampling for Regret Minimization in Extensive Games NeurIPS 2009 Bayesian Exponential Family PCA NeurIPS 2008