Stochastic Processes

Trustworthy Monte Carlo NeurIPS 2022 Tuning-Free Generalized Hamiltonian Monte Carlo AISTATS 2022 When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint JMLR 2022 An Adaptive-MCMC Scheme for Setting Trajectory Lengths in Hamiltonian Monte Carlo AISTATS 2021 Analysis of high-dimensional Continuous Time Markov Chains using the Local Bouncy Particle Sampler JMLR 2021 A Structured Observation Distribution for Generative Biological Sequence Prediction and Forecasting ICML 2021 Bayesian Quadrature on Riemannian Data Manifolds ICML 2021 Bounding Causal Effects on Continuous Outcome AAAI 2021 Calibrated Adaptive Probabilistic ODE Solvers AISTATS 2021 Compressed Maximum Likelihood ICML 2021 Consensus-Based Optimization on the Sphere: Convergence to Global Minimizers and Machine Learning JMLR 2021 Couplings for Multinomial Hamiltonian Monte Carlo AISTATS 2021 Detection of Signal in the Spiked Rectangular Models ICML 2021 Diffusion Source Identification on Networks with Statistical Confidence ICML 2021 Efficient Sampling of Dependency Structure EMNLP 2021 Exponential Reduction in Sample Complexity with Learning of Ising Model Dynamics ICML 2021 High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm JMLR 2021 Hoeffding's Inequality for General Markov Chains and Its Applications to Statistical Learning JMLR 2021 Implicit Langevin Algorithms for Sampling From Log-concave Densities JMLR 2021 Inferring serial correlation with dynamic backgrounds ICML 2021 Kernel Stein Discrepancy Descent ICML 2021 Learning in Matrix Games can be Arbitrarily Complex COLT 2021 Learning Stochastic Behaviour from Aggregate Data ICML 2021 Loop Estimator for Discounted Values in Markov Reward Processes AAAI 2021 Multi-stream based marked point process ACML 2021