Stochastic Processes

Multi-agent coverage control with transient behavior consideration L4DC 2024 Multimarginal Generative Modeling with Stochastic Interpolants ICLR 2024 Multi-times Monte Carlo Rendering for Inter-reflection Reconstruction NeurIPS 2024 NARUTO: Neural Active Reconstruction from Uncertain Target Observations CVPR 2024 Natural Evolution-based Dual-Level Aggregation for Temporal Knowledge Graph Reasoning EMNLP 2024 Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model NeurIPS 2024 Negative-Binomial Randomized Gamma Dynamical Systems for Heterogeneous Overdispersed Count Time Sequences IJCAI 2024 Negative Pre-aware for Noisy Cross-Modal Matching AAAI 2024 Neural McKean-Vlasov Processes: Distributional Dependence in Diffusion Processes AISTATS 2024 Neural Persistence Dynamics NeurIPS 2024 Neural structure learning with stochastic differential equations ICLR 2024 Neural Time-Reversed Generalized Riccati Equation AAAI 2024 Neuro-Symbolic Data Generation for Math Reasoning NeurIPS 2024 Noise-free Score Distillation ICLR 2024 Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization JMLR 2024 Nonasymptotic regret analysis of adaptive linear quadratic control with model misspecification L4DC 2024 Non-Autoregressive Machine Translation as Constrained HMM ACL 2024 Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients NeurIPS 2024 Non-Stationary Learning of Neural Networks with Automatic Soft Parameter Reset NeurIPS 2024 Nonstationary Sparse Spectral Permanental Process NeurIPS 2024 Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees JMLR 2024 Observation-Guided Diffusion Probabilistic Models CVPR 2024 On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions NeurIPS 2024 On Double Descent in Reinforcement Learning with LSTD and Random Features ICLR 2024 On Feynman-Kac training of partial Bayesian neural networks AISTATS 2024