Stochastic Processes

Solving inverse problem of Markov chain with partial observations NeurIPS 2013 An Autoregressive Approach to Nonparametric Hierarchical Dependent Modeling AISTATS 2012 Coding efficiency and detectability of rate fluctuations with non-Poisson neuronal firing NeurIPS 2012 Controlling Selection Bias in Causal Inference AISTATS 2012 Efficient Spike-Coding with Multiplicative Adaptation in a Spike Response Model NeurIPS 2012 Entangled Monte Carlo NeurIPS 2012 Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data NeurIPS 2012 Learning with Partially Absorbing Random Walks NeurIPS 2012 MCMC for continuous-time discrete-state systems NeurIPS 2012 Mixability in Statistical Learning NeurIPS 2012 Mixing Properties of Conditional Markov Chains with Unbounded Feature Functions NeurIPS 2012 Modelling Reciprocating Relationships with Hawkes Processes NeurIPS 2012 Nonconvex Penalization Using Laplace Exponents and Concave Conjugates NeurIPS 2012 On Average Reward Policy Evaluation in Infinite-State Partially Observable Systems AISTATS 2012 Quilting Stochastic Kronecker Product Graphs to Generate Multiplicative Attribute Graphs AISTATS 2012 Scalable Inference on Kingman’s Coalescent using Pair Similarity AISTATS 2012 Sparse Approximate Manifolds for Differential Geometric MCMC NeurIPS 2012 Stick-Breaking Beta Processes and the Poisson Process AISTATS 2012 The Coloured Noise Expansion and Parameter Estimation of Diffusion Processes NeurIPS 2012 Accelerated Adaptive Markov Chain for Partition Function Computation NeurIPS 2011 A General Linear Non-Gaussian State-Space Model: Identifiability, Identification, and Applications ACML 2011 Analytical Results for the Error in Filtering of Gaussian Processes NeurIPS 2011 Does an Efficient Calibrated Forecasting Strategy Exist? COLT 2011 Finite Time Analysis of Stratified Sampling for Monte Carlo NeurIPS 2011 Inference in continuous-time change-point models NeurIPS 2011