Sarthak Mittal
@sarthmit.bsky.social
📤 216
📥 23
📝 11
🚀 New Preprint! 🚀 In-Context Parametric Inference: Point or Distribution Estimators? Thrilled to share our work on inferring probabilistic model parameters explicitly conditioned on data, in collab with
@yoshuabengio.bsky.social
, Nikolay Malkin &
@glajoie.bsky.social
! 🔗
arxiv.org/abs/2502.11617
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In-Context Parametric Inference: Point or Distribution Estimators?
Bayesian and frequentist inference are two fundamental paradigms in statistical estimation. Bayesian methods treat hypotheses as random variables, incorporating priors and updating beliefs via Bayes' ...
https://arxiv.org/abs/2502.11617
7 months ago
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🚨 New Preprint! 🚨 We explore Amortized In-Context Bayesian Posterior Estimation with Niels,
@glajoie.bsky.social
, Priyank Jaini &
@marcusabrubaker.bsky.social
! 🔥 Amortized Conditional Modeling = key to success in large-scale models! We use it to estimate posteriors 🔑 📄
arxiv.org/abs/2502.06601
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Amortized In-Context Bayesian Posterior Estimation
Bayesian inference provides a natural way of incorporating prior beliefs and assigning a probability measure to the space of hypotheses. Current solutions rely on iterative routines like Markov Chain ...
https://arxiv.org/abs/2502.06601
7 months ago
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