← Optimization & Theory
Machine Learning › Optimization & Theory ›

Bayesian Inference

4821 directly classified papers

Papers per year

Papers

Learning Bayesian Networks with Thousands of Variables NIPS 2015
Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning NIPS 2015
MCMC for Variationally Sparse Gaussian Processes NIPS 2015
The Human Kernel NIPS 2015
Efficient Thompson Sampling for Online Matrix-Factorization Recommendation NIPS 2015
Bayesian Model Adaptation for Crowd Counts ICCV 2015
Softstar: Heuristic-Guided Probabilistic Inference NIPS 2015
Variational Consensus Monte Carlo NIPS 2015
Bounding the Cost of Search-Based Lifted Inference NIPS 2015
Finite-Time Analysis of Projected Langevin Monte Carlo NIPS 2015
Variational Dropout and the Local Reparameterization Trick NIPS 2015
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators NIPS 2015
Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference NIPS 2015
A Complete Recipe for Stochastic Gradient MCMC NIPS 2015
Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families NIPS 2015
Probabilistic Line Searches for Stochastic Optimization NIPS 2015
Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling NIPS 2015
Measuring Sample Quality with Stein's Method NIPS 2015
Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions NIPS 2015
A Gaussian Process Latent Variable Model for BRDF Inference ICCV 2015
Probability Occupancy Maps for Occluded Depth Images CVPR 2015
Bayesian Active Model Selection with an Application to Automated Audiometry NIPS 2015
Cross-Domain Matching for Bag-of-Words Data via Kernel Embeddings of Latent Distributions NIPS 2015
A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure NIPS 2015
Multi-Conditional Latent Variable Model for Joint Facial Action Unit Detection ICCV 2015