Statistical Learning
Interpretable Sequence Learning for COVID-19 Forecasting
Neural Information Processing Systems
Explainability is valuable to ensure that the model's forecasts are credible
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Improved Variational Bayesian Phylogenetic Inference with Normalizing Flows
Neural Information Processing Systems
We show that VBPI-NF significantly improves upon the vanilla VBPI on a benchmark of challenging real data Bayesian phylogenetic inference problems.
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STORM +: Fully Adaptive SGD with Momentum for Nonconvex Optimization
Neural Information Processing Systems
The most popular approach to handling such problems is variance reduction techniques, which are also known to obtain tight convergence rates, matching the lower bounds in this case.
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