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Stochastic Processes

92 directly classified papers

Papers per year

Papers

Local Dependence Graphs for Discrete Time Processes CLEAR 2023
Instrumental Processes Using Integrated Covariances CLEAR 2023
Separate but Equal: Equality in Belief Propagation for Single Cycle Graphs AAAI 2023
Initialization Noise in Image Gradients and Saliency Maps CVPR 2023
Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations AAAI 2023
Aligned Diffusion Schrödinger Bridges UAI 2023
Sampling from Arbitrary Functions via PSD Models AISTATS 2022
Power-Law Escape Rate of SGD ICML 2022
FlowHMM: Flow-based continuous hidden Markov models NIPS 2022
Anytime Information Cascade Popularity Prediction via Self-Exciting Processes ICML 2022
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint JMLR 2022
The Spatio-Temporal Poisson Point Process: A Simple Model for the Alignment of Event Camera Data ICCV 2021
Loop Estimator for Discounted Values in Markov Reward Processes AAAI 2021
Scaling up Continuous-Time Markov Chains Helps Resolve Underspecification NIPS 2021
Optimal prediction of Markov chains with and without spectral gap NIPS 2021
Inferring serial correlation with dynamic backgrounds ICML 2021
Learning in Matrix Games can be Arbitrarily Complex COLT 2021
Stable Online Control of Linear Time-Varying Systems L4DC 2021
Exponential Reduction in Sample Complexity with Learning of Ising Model Dynamics ICML 2021
Stability and Identification of Random Asynchronous Linear Time-Invariant Systems L4DC 2021
Learning Stochastic Behaviour from Aggregate Data ICML 2021
System Identification with Time-Aware Neural Sequence Models AAAI 2020
Stable Reinforcement Learning with Unbounded State Space L4DC 2020
Why Are Learned Indexes So Effective? ICML 2020
Residual Neural Processes AAAI 2020