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I maintain a (possibly outdated) paper list for out-of-distribution generalization here (thanks for Irina’s help!).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

Notes

• 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