Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: Generalizing Hamiltonian Monte Carlo with Neural Networks
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
MARKOV CHAIN MONTE CARLO METHODS: COMPUTATION AND INFERENCE
Particle Markov chain Monte Carlo methods
Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference
Stochastic Gradient MCMC Methods for Hidden Markov Models
Langevin-gradient parallel tempering for Bayesian neural learning
markov chain monte carlo and variational inference : bridging the gap .
Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions
A simple introduction to Markov Chain Monte–Carlo sampling
Variational inference for Monte Carlo objectives
Markov Chain Monte Carlo Method and Its Application
Practical Variational Inference for Neural Networks
Markov chain Monte Carlo without likelihoods
Gaussian Processes to Speed up Hybrid Monte Carlo for Expensive Bayesian Integrals
Learning Deep Generative Models with Doubly Stochastic MCMC
Learning Deep Generative Models With Doubly Stochastic Gradient MCMC
Adaptive Markov Chain Monte Carlo: Theory and Methods
Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization
Firefly Monte Carlo: Exact MCMC with Subsets of Data
Learning Deep Boltzmann Machines using Adaptive MCMC
Performance Comparison between Relational and Object-Oriented Databases
Statistical body height estimation from a single image
Card-660: Cambridge Rare Word Dataset - a Reliable Benchmark for Infrequent Word Representation Models
action recognition with dynamic image networks .
On the importance of initialization and momentum in deep learning