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stat.ML2022
Neural Continuous-Time Markov Models
Majerle Reeves, Harish S. Bhat
Continuous-time Markov chains are used to model stochastic systems where transitions can occur at irregular times, e.g., birth-death processes, chemical reaction networks, populati…
stat.ML2021
Equity-Directed Bootstrapping: Examples and Analysis
Harish S. Bhat, Majerle E. Reeves, Sidra Goldman-Mellor
When faced with severely imbalanced binary classification problems, we often train models on bootstrapped data in which the number of instances of each class occur in a more favora…
stat.ML2020
Estimating Vector Fields from Noisy Time Series
Harish S. Bhat, Majerle Reeves, Ramin Raziperchikolaei
While there has been a surge of recent interest in learning differential equation models from time series, methods in this area typically cannot cope with highly noisy data. We bre…