Overview of Stochastic Gradient Langevin Dynamics (SGLD) and examples of algorithms and implementations
Stochastic Gradient Langevin Dynamics（SGLD）
Stochastic Gradient Langevin Dynamics (SGLD) is a stochastic optimi...
数学:Mathematics
How to deal with singularities in Newton’s method
How to deal with singularities in Newton's method
Newton's method, also described in ‘Overview of Newton's meth...
KL divergence constraint
KL divergence constraint
The KL divergence (Kullback-Leibler Divergence) is an asymmetric measure of simil...
Alternative methods of numerical differentiation in the calculation of derivatives of Newton’s method
Alternative methods of numerical differentiation in the calculation of derivatives of Newton's method
The Newto...
Epistemic uncertainty and AI complementation
epistemic uncertainty
Epistemic Uncertainty refers to uncertainty arising from a lack or incompleteness of...
Rescaling of Newton’s method
Rescaling of Newton's method
Rescaling in Newtonian methods is one of the methods used in numerical optimisatio...
Temporal Graph Neural Network overview and implementation examples
Temporal Graph Neural Network
Temporal Graph Neural Networks (TGNNs) are deep learning methods for process...
Aleatory uncertainty and AI-based solutions
Aleatory Uncertainty
Aleatory Uncertainty will mainly refer to uncertainty caused by natural phenomena and...
How to improve linear convergence in Newton’s method
How to improve linear convergence in Newton's method
The Newton method, also described in ‘Overview of the Newt...
Overview of genetic algorithms, application examples, and implementation examples
Overview of genetic algorithms
Genetic algorithm (GA) is a type of evolutionary computation, and is an optimiza...