Optimization and Machine Learning Lab

Publication

  1. E. F. Arruda; T. Sharma; R. e A. Alexandre; S. S. Thomas, “ Epidemic Control Modeling using Parsimonious Models and Markov Decision Processes,” in arXiv:2206.13910, 2022.[Code]
  1. S. S. Thomas; J. Palandri; M. Lakehal-ayat; P. Chakravarty; F. Wolf-Monheim; M. B.Blaschko, “ Kinematics Design of a MacPherson Suspension Architecture based on Bayesian Optimization,” in IEEE Transactions on Cybernetics (in press), 2021.
  2. R. Giriraj; S. S. Thomas, “ Causal Discovery in Knowledge Graphs by Exploiting Asymmetric Properties of Non-Gaussian Distributions,” in arXiv:2106.01043, 2021. [Code]
  3. M. A. Solis; S. S. Thomas, “ Generalized State-Feedback Controller Synthesis for Underactuated Systems through Bayesian Optimization,” in arXiv:2103.17158, 2021. [Code]
  4. E. F. Arruda; R. e A. Alexandre; M. D. Fragoso; João B. R. do val; S. S. Thomas, “A Novel Stochastic Epidemic Model with Application to COVID-19,” in arXiv:2102.08213, 2021.
  1. O. T. James; S. S. Thomas, “ Bayesian Optimized Event Based Epidemic Modeling in India,” in arXiv:2010.01280, 2020.
  2. A. M. Paul; S. S. Thomas, “Multifaceted COVID-19 Outbreak,” in arXiv:2008.12127, 2020.
  1. S. S. Thomas; J. Palandri; M. Lakehal-ayat; P. Chakravarty; F. Wolf-Monheim;M. B. Blaschko,“Designing MacPherson Suspension Architectures using Bayesian Optimization,” 28th Belgian Dutch Conference on Machine Learning, Brussels, Belgium, Nov 6-8, 2019.