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Stochastic Processes

373 directly classified papers

Papers per year

Papers

Piecewise deterministic generative models NIPS 2024
Testing exchangeability by pairwise betting AISTATS 2024
Distributional regression: CRPS-error bounds for model fitting, model selection and convex aggregation NIPS 2024
Queueing Matching Bandits with Preference Feedback NIPS 2024
Constrained Sampling with Primal-Dual Langevin Monte Carlo NIPS 2024
autoMALA: Locally adaptive Metropolis-adjusted Langevin algorithm AISTATS 2024
Minimum Entropy Coupling with Bottleneck NIPS 2024
Measuring Sample Quality in Algorithms for Intractable Normalizing Function Problems JMLR 2024
Learning from many trajectories JMLR 2024
Optimal Scaling for the Proximal Langevin Algorithm in High Dimensions JMLR 2024
Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels AISTATS 2024
Hawkes-Enhanced Spatial-Temporal Hypergraph Contrastive Learning Based on Criminal Correlations AAAI 2024
Approximating Intersections and Differences Between Linear Statistical Shape Models Using Markov Chain Monte Carlo WACV 2024
A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers NIPS 2024
On the Statistical Efficiency of Mean-Field Reinforcement Learning with General Function Approximation AISTATS 2024
Pareto Smoothed Importance Sampling JMLR 2024
Quasi-Bayes meets Vines NIPS 2024
Generative Fractional Diffusion Models NIPS 2024
Learning multivariate temporal point processes via the time-change theorem AISTATS 2024
Low Degree Hardness for Broadcasting on Trees NIPS 2024
Statistical Comparisons of Classifiers by Generalized Stochastic Dominance JMLR 2023
Limits of Dense Simplicial Complexes JMLR 2023
Infinite-dimensional optimization and Bayesian nonparametric learning of stochastic differential equations JMLR 2023
Concentration analysis of multivariate elliptic diffusions JMLR 2023
FLIP: A Utility Preserving Privacy Mechanism for Time Series JMLR 2023