stochastic process

Hodge-Compositional Edge Gaussian Processes AISTATS 2024 Inferring stochastic low-rank recurrent neural networks from neural data NeurIPS 2024 Infinite-Dimensional Diffusion Models JMLR 2024 Is Score Matching Suitable for Estimating Point Processes? NeurIPS 2024 Langevin Policy for Safe Reinforcement Learning ICML 2024 Learning from many trajectories JMLR 2024 Learning multivariate temporal point processes via the time-change theorem AISTATS 2024 Log-concave Sampling from a Convex Body with a Barrier: a Robust and Unified Dikin Walk NeurIPS 2024 Lookback Prophet Inequalities NeurIPS 2024 MINDE: Mutual Information Neural Diffusion Estimation ICLR 2024 Minimum Entropy Coupling with Bottleneck NeurIPS 2024 On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models ICLR 2024 Online Markov Decision Processes Configuration with Continuous Decision Space AAAI 2024 Optimal Scaling for the Proximal Langevin Algorithm in High Dimensions JMLR 2024 Parametric model reduction of mean-field and stochastic systems via higher-order action matching NeurIPS 2024 Piecewise deterministic generative models NeurIPS 2024 Probabilistic size-and-shape functional mixed models NeurIPS 2024 Probably approximately correct stability of allocations in uncertain coalitional games with private sampling L4DC 2024 Pure Differential Privacy for Functional Summaries with a Laplace-like Process JMLR 2024 QGym: Scalable Simulation and Benchmarking of Queuing Network Controllers NeurIPS 2024 Queueing Matching Bandits with Preference Feedback NeurIPS 2024 Retro-fallback: retrosynthetic planning in an uncertain world ICLR 2024 Reverse Diffusion Monte Carlo ICLR 2024 Seed Selection in the Heterogeneous Moran Process IJCAI 2024 Slowly Changing Adversarial Bandit Algorithms are Efficient for Discounted MDPs ALT 2024