Bayesian Inference, Monte Carlo, Probabilistic Models, Stan
Probabilistic Consistency in Machine Learning and Its Connection to Uncertainty Quantification
arxiv.org·2d
(1) Fitting hierarchical models in genetics, (2) A Stan model that runs faster with 400,000 latent parameters, (3) Super-scalable penalized maximum likelihood i...
statmodeling.stat.columbia.edu·15h
Good Learners Think Their Thinking: Generative PRM Makes Large Reasoning Model More Efficient Math Learner
arxiv.org·3h
LVM-GP: Uncertainty-Aware PDE Solver via coupling latent variable model and Gaussian process
arxiv.org·1d
Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems
arxiv.org·1d
Python Beginner's Guide to Processing Data
howtogeek.com·16h
Loading...Loading more...