Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper
Query: Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring
Bayesian Learning via Stochastic Gradient Langevin Dynamics
Stochastic Gradient MCMC Methods for Hidden Markov Models
Particle Markov chain Monte Carlo methods
Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach
Particle Gibbs with Ancestor Sampling
Sampling for Bayesian Program Learning.
Stan: A Probabilistic Programming Language for Bayesian Inference and Optimization
A Bayesian Perspective on Generalization and Stochastic Gradient Descent
Streaming Variational Bayes
Automatic Variational Inference in Stan
An adaptive learning rate for stochastic variational inference
Application of Bayesian approach to numerical methods of global and stochastic optimization
Fast collapsed gibbs sampling for latent dirichlet allocation
Bayesian Learning via Stochastic Dynamics
Why is Posterior Sampling Better than Optimism for Reinforcement Learning
Sticking the Landing: An Asymptotically Zero-Variance Gradient Estimator for Variational Inference
Variational Bayesian Inference : Algorithms for Sparse Gaussian Processes and Theoretical Bounds
PAC-Bayesian Stochastic Model Selection
Simulation studies in optimistic bayesian sampling in contextual-bandit problems
A tutorial on adaptive MCMC
Design of Low Noise Amplifiers at 10 GHZ and 15 GHZ for Wireless Communication Systems
New pre-estimation algorithm for FMCW radar systems using the Matrix Pencil Method
Semi-Supervised Learning Using Gaussian Fields and Harmon ic Functions
dopamine : generalization and bonuses .
Data mining workflow templates for intelligent discovery assistance and auto-experimentation