University of Florida | Department of Physics
Physics 7097 "Machine Learning"
Fall 2020
Project Assignments

Below is the list of students (in alphabetical order by their initials) and the selected topics.

  • 01. JA: "OPTICS clustering"
  • 02. SB: "Voting Classifier and Voting Regressor"
  • 03. DC: "Novelty and Outlier Detection"
  • 04. AD: "Predicting cryogenic thermalization with neural networks"
  • 05. PE: "Expanding LISA Optical Pathlength Noise Simulations" (regression and dimensionality reduction)
  • 06. SG: "Affinity propagation clustering"
  • 07. NG: "Using topological data science to detect cosmic voids"
  • 08. SKa: "A basic time series forecasting of the stock market using LSTM"
  • 09. SKu: "Predicting match results in the English Premier League"
  • 10. LL: "The Winning Formula"
  • 11. IM: "Recovering Binary Black Hole Mergers with Convolutional Neural Networks"
  • 12. TM: "Enhancing detection of Gravitational waves with Machine Learning" (uses XGBoost classifier)
  • 13. VR: "Graph Neural Networks"
  • 14. NR: "Binary classification of Higgs from 4 lepton background processes using Neural network""
  • 15. AR: "Transformer modelling in music or something easier"
  • 16. MS: "Manifold learning: t-SNE"
  • 17. BS: "Dispersed Multiphase Flow Generation using 3D Steerable CNN"
  • 18. SS: "Hierarchical clustering"
  • 19. CS: "Decomposing signals in components"
  • 20. LT: "Glitch classification using a convolutional autoencoder"

Below are some topics which we did not get a chance to mention or discuss in detail in class. They are all implemented in scikit-learn and make for suitabe final projects. You will need to briefly explain the basic idea, show some simple example as an illustration of a typical implementation, and present a performance comparison against a competitor method.

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