Publications on System Identification and Propagation for ODEs and SDEs:

• C. Kello, H. S. Bhat, C. Alviar, and M. A. Turner (2024)
  Hierarchical Timescales and Nested Process Composition.
  [PsyArXiv]
• M. Reeves and H. S. Bhat (2023)
  Neural Continuous-Time Markov Models.
  Proc. 2023 SICE International Symposium on Control Systems, pp. 76-83.
  [proceedings] [arXiv]
• H. S. Bhat (2022)
  Drift Identification for Lévy alpha-Stable Stochastic Systems.
  [arXiv]
• H. S. Bhat (2021)
  System Identification via the Adjoint Method.
  Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, pp. 1317-1321.
  [proceedings]
  
• R. K. Yoon, H. S. Bhat, and B. Osting (2021)
  A non-autonomous equation discovery method for time signal classification.
  SIAM Journal on Applied Dynamical Systems 21(1): 33-59.
  [arXiv] [journal]
• H. S. Bhat, M. Reeves, and R. Raziperchikolaei (2020)
  Estimating Vector Fields from Noisy Time Series.
  Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, pp. 509-606.
  [pdf] [proceedings]
  
• H. S. Bhat (2019)
  Learning and Interpreting Potentials for Classical Hamiltonian Systems.
  In: International Workshops of ECML PKDD 2019, Proceedings, Part I,
  Communications in Computer and Information Science 1167, pp. 217-228.
  [arXiv] [proceedings]
• H. S. Bhat and S. Rawat (2019)
  Learning Stochastic Dynamical Systems via Bridge Sampling.
  In: Advanced Analytics and Learning on Temporal Data (AALTD 2019),
  Lecture Notes in Computer Science 11986, pp. 183-198.
  [pdf] [proceedings]
• R. Raziperchikolaei and H. S. Bhat (2019)
  A Block Coordinate Descent Proximal Method for Simultaneous Filtering and Parameter Estimation.
  Proceedings of the 36th International Conference on Machine Learning, PMLR 97, pp. 5380-5388.
  [abs] [pdf] [supplementary material] [code]
• R. Dale and H. S. Bhat (2018)
  Equations of mind: Data science for inferring nonlinear dynamics of socio-cognitive systems.
  Cognitive Systems Research, 52, pp. 275-290.
  [journal]
• H. S. Bhat, R. W. M. A. Madushani, and S. Rawat (2018)
  Parameter Inference for Stochastic Differential Equations with Density Tracking by Quadrature.
  In: Statistics and Simulation. Springer Proceedings in Mathematics & Statistics. 231, pp. 99-113.
  [proceedings]
• H. S. Bhat and R. W. M. A. Madushani (2016)
  Density tracking by quadrature for stochastic differential equations.
  [arXiv]
• H. S. Bhat, R. W. M. A. Madushani, and S. Rawat (2017)
  Bayesian inference of stochastic pursuit models from basketball tracking data.
  In: Bayesian Statistics in Action. Springer Proceedings in Mathematics & Statistics. 194, pp.127-137.
  [pdf] [proceedings]
• H. S. Bhat, R. W. M. A. Madushani, and S. Rawat (2016)
  Scalable SDE filtering and inference with Apache Spark.
  Proceedings of the 5th International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications (KDD BigMine '16), PMLR 53, pp. 18-34.
  [pdf] [proceedings]
• H. S. Bhat and R. W. M. A. Madushani (2016)
  Nonparametric adjoint-based inference for stochastic differential equations.
  Proc. 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA), pp. 798-807.
  [pdf] [proceedings]
• H. S. Bhat and R. W. M. A. Madushani (2015)
  Computing the density function for a nonlinear stochastic delay system.
  Proc. 12th IFAC Workshop on Time Delay Systems (TDS 2015), IFAC-PapersOnLine, 48 (12), pp. 316-321.
  [pdf] [proceedings]
• H. S. Bhat (2014)
  Algorithms for linear stochastic delay differential equations.
  In: Topics in Statistical Simulation. Springer Proceedings in Mathematics & Statistics. 114, pp. 57-65
  [pdf] [proceedings]
• H. S. Bhat and N. Kumar (2012)
  Spectral solution of delayed random walks.
  Physical Review E, 86 (4) 045701.
  [pdf] [journal]