← Optimization & Theory
Machine Learning › Optimization & Theory ›

Stochastic Processes

2667 directly classified papers

Papers per year

Papers

Estimators of Entropy and Information via Inference in Probabilistic Models AISTATS 2022
Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants NIPS 2022
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations AISTATS 2022
Fast and Scalable Spike and Slab Variable Selection in High-Dimensional Gaussian Processes AISTATS 2022
Nonlinear MCMC for Bayesian Machine Learning NIPS 2022
Risk-Aware Stochastic Shortest Path AAAI 2022
Structuring Uncertainty for Fine-Grained Sampling in Stochastic Segmentation Networks NIPS 2022
Metrics of Calibration for Probabilistic Predictions JMLR 2022
Scalable Gaussian-process regression and variable selection using Vecchia approximations JMLR 2022
Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence JMLR 2022
Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling JMLR 2022
Mappings for Marginal Probabilities with Applications to Models in Statistical Physics JMLR 2022
Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement Learning ICML 2022
USHER: Unbiased Sampling for Hindsight Experience Replay CORL 2022
Learning Expected Emphatic Traces for Deep RL AAAI 2022
An Efficient Sampling Algorithm for Non-smooth Composite Potentials JMLR 2022
Efficient Inference for Dynamic Flexible Interactions of Neural Populations JMLR 2022
Three rates of convergence or separation via U-statistics in a dependent framework JMLR 2022
Contrastive Conditional Neural Processes CVPR 2022
Kernel Packet: An Exact and Scalable Algorithm for Gaussian Process Regression with Matérn Correlations JMLR 2022
Time Varying Regression with Hidden Linear Dynamics L4DC 2022
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting JMLR 2022
Beyond Sub-Gaussian Noises: Sharp Concentration Analysis for Stochastic Gradient Descent JMLR 2022
Optimal Control with Learning on the Fly: System with Unknown Drift L4DC 2022
Neural Mean Discrepancy for Efficient Out-of-Distribution Detection CVPR 2022