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Found 6 papers, 1 papers with code
Quantum Bayesian Computation
Quantum Bayesian Computation (QBC) is an emerging field that levers the computational gains available from quantum computers to provide an exponential speed-up in Bayesian computation.
Merging Two Cultures: Deep and Statistical Learning
We show that prediction, interpolation and uncertainty quantification can be achieved using probabilistic methods at the output layer of the model.
Bayesian Inference for Gamma Models
We use the theory of normal variance-mean mixtures to derive a data augmentation scheme for models that include gamma functions.
Data Augementation with Polya Inverse Gamma
We use the theory of normal variance-mean mixtures to derive a data augmentation scheme for models that include gamma functions.
Deep Learning in Characteristics-Sorted Factor Models
This paper presents an augmented deep factor model that generates latent factors for cross-sectional asset pricing.
Methodology
Sparse Regularization in Marketing and Economics
Alpha-norm, in contrast to lasso and ridge regularization, jumps to a sparse solution.
