• Object detection with Deep CNN
  • Transfer learning and hidden representations in DNN
  • Deep Boltzmann Machines
  • Monte Carlo Sampling
  • Other sampling strategies (importance sampling)
  • Probabilistic Programming 
  • Gaussian Processes (sparsification, Deep Gaussian Processes)
  • Randomized projections for kernel machines (Ali Rahimi)
  • Handwritten recognition
  • Bayesian Generalised Linear Models
  • Variational methods for inference (mean field in Bayesian Networks, variational explanation of Loopy Belief Propagation)
  • Generative Models for Images using DL
  • RNN for financial time series
  • Neural ODEs
  • Adversarial Examples and Geometrical properties of Data Manifolds
  • Other topics (your call)
Last modified: Thursday, 9 May 2019, 3:07 PM