Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: Quasi-Newton Hamiltonian Monte Carlo
Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm
Stochastic Gradient Riemannian Langevin Dynamics on the Probability Simplex
Particle Gibbs with Ancestor Sampling
dram : efficient adaptive mcmc .
On sequential Monte Carlo sampling methods for Bayesian filtering
Markov Chain Monte Carlo Convergence Diag-nostics: A Comparative Review
Two Methods For Wild Variational Inference
Learning to Optimize Via Posterior Sampling
An optimal algorithm for Monte Carlo estimation
The Kolmogorov sampler
Learning Deep Generative Models With Doubly Stochastic Gradient MCMC
Markov Chain Monte Carlo Simulation Methods in Econometrics
Application of Bayesian approach to numerical methods of global and stochastic optimization
C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching
Learning Deep Generative Models with Doubly Stochastic MCMC
Markov Chain Sampling Methods for Dirichlet Process Mixture Models
sequential monte carlo samplers .
Monte Carlo Methods in Statistical Mechanics: Foundations and New Algorithms
Ergodicity of Approximate MCMC Chains with Applications to Large Data Sets
A tutorial on adaptive MCMC
Guardian of the HAN: Thwarting Mobile Attacks on Smart-Home Devices Using OS-level Situation Awareness
Deep convolutional neural networks for LVCSR
FIREMAN: a toolkit for firewall modeling and analysis
Natural Light and Productivity: Analyzing the Impacts of Daylighting on Students’ and Workers’ Health and Alertness