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Stochastic Processes

2667 directly classified papers

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Papers

Slice Sampling on Hamiltonian Trajectories ICML 2016
Measuring the reliability of MCMC inference with bidirectional Monte Carlo NIPS 2016
Spectral Learning of Dynamic Systems from Nonequilibrium Data NIPS 2016
Synthesis of MCMC and Belief Propagation NIPS 2016
Multiple-Play Bandits in the Position-Based Model NIPS 2016
Variance Reduction in Stochastic Gradient Langevin Dynamics NIPS 2016
Combinatorial semi-bandit with known covariance NIPS 2016
The Forget-me-not Process NIPS 2016
Density Evolution in the Degree-correlated Stochastic Block Model COLT 2016
Monte Carlo Markov Chain Algorithms for Sampling Strongly Rayleigh Distributions and Determinantal Point Processes COLT 2016
Statistical Modeling of Speaker’s Voice with Temporal Co-Location for Active Voice Authentication INTERSPEECH 2016
A state-space model of cross-region dynamic connectivity in MEG/EEG NIPS 2016
Consistency and Fluctuations For Stochastic Gradient Langevin Dynamics JMLR 2016
Hawkes Processes with Stochastic Excitations ICML 2016
Structure Discovery in Bayesian Networks by Sampling Partial Orders JMLR 2016
Efficient Computation of Gaussian Process Regression for Large Spatial Data Sets by Patching Local Gaussian Processes JMLR 2016
A Variational Approach to Path Estimation and Parameter Inference of Hidden Diffusion Processes JMLR 2016
Nonparametric Network Models for Link Prediction JMLR 2016
On Mixtures of Markov Chains NIPS 2016
Adaptive Concentration Inequalities for Sequential Decision Problems NIPS 2016
Structure Learning in Bayesian Networks of a Moderate Size by Efficient Sampling JMLR 2016
Parallel Markov Chain Monte Carlo via Spectral Clustering AISTATS 2016
Mondrian Forests for Large-Scale Regression when Uncertainty Matters AISTATS 2016
Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks NIPS 2016
Convergence of Stochastic Gradient Descent for PCA ICML 2016