Interested in automatic inductive bias selection using Bayesian tools.
As previously, the message is: Causal discovery requires assumptions, and Bayes enables soft, realistic assumptions. Good Bayesian inference then leads to good performance. 1/3
We propose a Bayesian causal model that allows for scalable causal discovery without restrictive model assumptions.
Paper: arxiv.org/abs/2411.10154
Code: github.com/Anish144/Con...
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As previously, the message is: Causal discovery requires assumptions, and Bayes enables soft, realistic assumptions. Good Bayesian inference then leads to good performance. 1/3
📅 Today Fri, Dec 13
⏰ 11 a.m. – 2 p.m. PST
📍 East Exhibit Hall A-C, #4710 (ALL the way in the back I believe!)
w/ @mvdw.bsky.social @pimdh.bsky.social
Come say hi! 👋
📅 Today Fri, Dec 13
⏰ 11 a.m. – 2 p.m. PST
📍 East Exhibit Hall A-C, #4710 (ALL the way in the back I believe!)
w/ @mvdw.bsky.social @pimdh.bsky.social
Come say hi! 👋