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Mathematics
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Stochastic Processes
92 directly classified papers
Papers per year
2003: 1
2006: 1
2008: 1
2009: 3
2010: 1
2011: 3
2012: 2
2013: 1
2014: 3
2015: 4
2016: 6
2017: 3
2018: 4
2019: 9
2020: 4
2021: 10
2022: 5
2023: 10
2024: 17
2025: 4
Papers
Learning Neural Jump Stochastic Differential Equations with Latent Graph for Multivariate Temporal Point Processes
IJCAI 2025
Sampling and Estimation on Manifolds using the Langevin Diffusion
JMLR 2025
Losing Momentum in Continuous-time Stochastic Optimisation
JMLR 2025
VeRecycle: Reclaiming Guarantees from Probabilistic Certificates for Stochastic Dynamical Systems after Change
IJCAI 2025
Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly Sampled Time Series
NIPS 2024
When are dynamical systems learned from time series data statistically accurate?
NIPS 2024
Measuring Sample Quality in Algorithms for Intractable Normalizing Function Problems
JMLR 2024
Learning Macroscopic Dynamics from Partial Microscopic Observations
NIPS 2024
Computing the Bias of Constant-step Stochastic Approximation with Markovian Noise
NIPS 2024
Learning the Infinitesimal Generator of Stochastic Diffusion Processes
NIPS 2024
Deep Learning for Computing Convergence Rates of Markov Chains
NIPS 2024
Correlated Binomial Process
COLT 2024
Identifiability Analysis of Linear ODE Systems with Hidden Confounders
NIPS 2024
Continuous-Time Graph Representation with Sequential Survival Process
AAAI 2024
From Biased to Unbiased Dynamics: An Infinitesimal Generator Approach
NIPS 2024
Spectral Learning of Shared Dynamics Between Generalized-Linear Processes
NIPS 2024
Probabilistic size-and-shape functional mixed models
NIPS 2024
Approximating Intersections and Differences Between Linear Statistical Shape Models Using Markov Chain Monte Carlo
WACV 2024
Correction to "Wasserstein distance estimates for the distributions of numerical approximations to ergodic stochastic differential equations"
JMLR 2024
An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations
NIPS 2024
Log-concave Sampling from a Convex Body with a Barrier: a Robust and Unified Dikin Walk
NIPS 2024
The $k$-Cap Process on Geometric Random Graphs
COLT 2023
Fast Computation of Branching Process Transition Probabilities via ADMM
AISTATS 2023
Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations
AAAI 2023
Randomized geometric tools for anomaly detection in stock markets
AISTATS 2023
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