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Stochastic Processes

2,667 papers

Papers per year

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Papers

Switching Linear Dynamics for Variational Bayes Filtering ICML 2019
Stein Point Markov Chain Monte Carlo ICML 2019
Semi-Cyclic Stochastic Gradient Descent ICML 2019
Amortized Monte Carlo Integration ICML 2019
A Statistical Investigation of Long Memory in Language and Music ICML 2019
Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models ICML 2019
Contextual Multi-armed Bandit Algorithm for Semiparametric Reward Model ICML 2019
Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement ICML 2019
Kernel-Based Reinforcement Learning in Robust Markov Decision Processes ICML 2019
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations ICML 2019
Understanding MCMC Dynamics as Flows on the Wasserstein Space ICML 2019
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions ICML 2019
Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards ICML 2019
Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models ICML 2019
A Wrapped Normal Distribution on Hyperbolic Space for Gradient-Based Learning ICML 2019
Nonlinear Distributional Gradient Temporal-Difference Learning ICML 2019
A Contrastive Divergence for Combining Variational Inference and MCMC ICML 2019
Deep Gaussian Processes with Importance-Weighted Variational Inference ICML 2019
Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data ICML 2019
Scalable Training of Inference Networks for Gaussian-Process Models ICML 2019
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks ICML 2019
Transfer of Samples in Policy Search via Multiple Importance Sampling ICML 2019
Learning Hawkes Processes Under Synchronization Noise ICML 2019
Graph Convolutional Gaussian Processes ICML 2019
On the statistical rate of nonlinear recovery in generative models with heavy-tailed data ICML 2019