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Stochastic Processes

373 directly classified papers

Papers per year

Papers

High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm JMLR 2021
Diffusion Source Identification on Networks with Statistical Confidence ICML 2021
Bayesian Quadrature on Riemannian Data Manifolds ICML 2021
Training Multi-Object Detector by Estimating Bounding Box Distribution for Input Image ICCV 2021
Inferring serial correlation with dynamic backgrounds ICML 2021
UNIPoint: Universally Approximating Point Processes Intensities AAAI 2021
Tight sampling and discarding bounds for scenario programs with an arbitrary number of removed samples L4DC 2021
Bounding Causal Effects on Continuous Outcome AAAI 2021
Couplings for Multinomial Hamiltonian Monte Carlo AISTATS 2021
Kernel Stein Discrepancy Descent ICML 2021
Privately Learning Markov Random Fields ICML 2020
Infinity Learning: Learning Markov Chains from Aggregate Steady-State Observations AAAI 2020
Constraing-Based Learning for Continous-Time Bayesian Networks PGM 2020
Infinitely deep neural networks as diffusion processes AISTATS 2020
Stable behaviour of infinitely wide deep neural networks AISTATS 2020
Simulator Calibration under Covariate Shift with Kernels AISTATS 2020
A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms AISTATS 2020
Memoryless Sequences for General Losses JMLR 2020
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients JMLR 2020
Asymptotic Analysis via Stochastic Differential Equations of Gradient Descent Algorithms in Statistical and Computational Paradigms JMLR 2020
Risk Bounds for Reservoir Computing JMLR 2020
Fast and Consistent Learning of Hidden Markov Models by Incorporating Non-Consecutive Correlations ICML 2020
Learning with Labeled and Unlabeled Multi-Step Transition Data for Recovering Markov Chain from Incomplete Transition Data IJCAI 2020
ASR-Free Pronunciation Assessment INTERSPEECH 2020
TellTail: Fast Scoring and Detection of Dense Subgraphs AAAI 2020