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stat.CO2025
Parallelizing MCMC Across the Sequence Length
David M. Zoltowski, Skyler Wu, Xavier Gonzalez +2
Markov chain Monte Carlo (MCMC) methods are foundational algorithms for Bayesian inference and probabilistic modeling. However, most MCMC algorithms are inherently sequential and t…
stat.CO2025
Are Statistical Methods Obsolete in the Era of Deep Learning? A Study of ODE Inverse Problems
Skyler Wu, Shihao Yang, S. C. Kou
In the era of AI, neural networks have become increasingly popular for modeling, inference, and prediction, largely due to their potential for universal approximation. With the pro…
stat.CO2024
Extracting Signal out of Chaos: Advancements on MAGI for Bayesian Analysis of Dynamical Systems
Skyler Wu
This work builds off the manifold-constrained Gaussian process inference (MAGI) method for Bayesian parameter inference and trajectory reconstruction of ODE-based dynamical systems…