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There’s a lot of confusion around uncertainty in machine learning. We argue the "aleatoric vs epistemic" view has contributed to this and present a rigorous alternative. #ICML2025 with @janundnik @eleanortrollope @markvanderwilk @adamefoster @tom_rainforth 1/5
Excited to be presenting this work at ICML! Our Bayesian method allows for causal discovery using more flexible assumptions that better reflect real-world data. Come chat to us: Tues 4:30pm East Exhibition Hall A-B E-1912 Paper: arxiv.org/abs/2411.10154
📢New #ICML2025 paper: "Continuous Bayesian Model Selection for Multivariate Causal Discovery". 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/Conti… 🧵1/14
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