Slides & Notes

I often write some unofficial manuscripts and slides to help collect my thoughts.

I maintain a resource list for GFlowNets here.

I maintain a (possibly outdated) paper list for out-of-distribution generalization here (thanks for Irina’s help!).

Talk Slides

  • At the intersection of probabilistic inference and exploration methods: link
  • Review of counterfactual representation learning: link
  • Review of out-of-distribution generalization: link
  • Introduction to causal inference: link
  • Review of learning in traditional cv methods: link
  • Review of reweight methods: link
  • Review of unlabeled data used in adversarial training: link
  • Some random papers sharing: link
  • One paper about off-policy evaluation: link
  • Review of normalizing flows: link
  • Review of capsule networks: link


  • Bayesian optimal experimental design: link
  • Kernelized Wasserstein gradient flow: link
  • Conformal inference basics: link
  • A way to unify different probabilistic inference approaches: link
  • Connection between adversarial robustness and other learning fields: link
  • Stochastic analysis: link
  • A review on interpretating deep neural network: link
  • A short survey on Image Inpainting: link