stochastic process

Kernel Trajectory Maps for Multi-Modal Probabilistic Motion Prediction CoRL 2019 Minimax Online Prediction of Varying Bernoulli Process under Variational Approximation ACML 2019 Neural Jump Stochastic Differential Equations NeurIPS 2019 Non-linear process convolutions for multi-output Gaussian processes AISTATS 2019 Online Algorithm for Unsupervised Sensor Selection AISTATS 2019 Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms NeurIPS 2019 On the statistical rate of nonlinear recovery in generative models with heavy-tailed data ICML 2019 Optimal Exploitation of Clustering and History Information in Multi-armed Bandit IJCAI 2019 Phase Transitions and Cyclic Phenomena in Bandits with Switching Constraints NeurIPS 2019 Privacy Amplification by Mixing and Diffusion Mechanisms NeurIPS 2019 Robust Online Matching with User Arrival Distribution Drift AAAI 2019 Sequential Neural Processes NeurIPS 2019 State-Augmentation Transformations for Risk-Sensitive Reinforcement Learning AAAI 2019 Structured Variational Inference in Continuous Cox Process Models NeurIPS 2019 The Functional Neural Process NeurIPS 2019 Variance Reduction for Reinforcement Learning in Input-Driven Environments ICLR 2019 Accelerating Stochastic Gradient Descent for Least Squares Regression COLT 2018 Concentration inequalities for empirical processes of linear time series JMLR 2018 Convergence of Value Aggregation for Imitation Learning AISTATS 2018 Counterfactual Resimulation for Causal Analysis of Rule-Based Models IJCAI 2018 Implicit Probabilistic Integrators for ODEs NeurIPS 2018 Latent Space Oddity: on the Curvature of Deep Generative Models ICLR 2018 Learning Continuous Time Bayesian Networks in Non-stationary Domains IJCAI 2018 Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification COLT 2018 Local Optimality and Generalization Guarantees for the Langevin Algorithm via Empirical Metastability COLT 2018