Really great and succinct talk! I'm learning about Causal Inference from a precision medicine context, and it's great to be exposed at a high level to the concepts in estimating causal effects from limited data using deep learning and bayesian model averaging on estimated DAGs. Thanks 👍
I really feel that the equations should be replaced with visualisation or at least explained more. In the end it is still glorified Bayes theorem and matrix multiplication :D. Great intent to show the latest works in any case, great work!
Really great and succinct talk! I'm learning about Causal Inference from a precision medicine context, and it's great to be exposed at a high level to the concepts in estimating causal effects from limited data using deep learning and bayesian model averaging on estimated DAGs. Thanks 👍
I really feel that the equations should be replaced with visualisation or at least explained more. In the end it is still glorified Bayes theorem and matrix multiplication :D. Great intent to show the latest works in any case, great work!
I understood absolutely nothing 😭. Guess I have much to learn
Showing a few practical cases would be nice, successful and not.
Super success super congrats. Keep up the good work. Please kindly more work on human level end to end real causal intelligent AI