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Found 4 papers, 2 papers with code
Nonlinear MCMC for Bayesian Machine Learning
We explore the application of a nonlinear MCMC technique first introduced in [1] to problems in Bayesian machine learning.
On the Regularity of Attention
Attention is a powerful component of modern neural networks across a wide variety of domains.
A Mathematical Theory of Attention
Attention is a powerful component of modern neural networks across a wide variety of domains.
Kalman Gradient Descent: Adaptive Variance Reduction in Stochastic Optimization
We introduce Kalman Gradient Descent, a stochastic optimization algorithm that uses Kalman filtering to adaptively reduce gradient variance in stochastic gradient descent by filtering the gradient estimates.
