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As you know, GauGAN is the following (from this post): GauGAN was a Microsoft Paint-style platform that let uses create landscape images, with the model then able to turn them into photorealistic ima …

That term exactly refers to the difference between two main paradigms in probability and statistics: Frequentism vs Bayesianism. You can find many texts for explaining the difference, for example [1] …

You can find a brief explanation of hierarchical feature selection in the following from "An Empirical Evaluation of Hierarchical Feature Selection Methods for Classification in Bioinformatics Dataset …

Yes, they can be related to underflow. Mathematically, we do not expect facing with division by zero when we have an expression $\frac{1}{\varepsilon}$ when $\varepsilon > 0$. However, in numerical so …

You can find a definition for "numerical stability" in mathworld wolframe: Numerical stability refers to how a malformed input affects the execution of an algorithm. In a numerically stable algorithm …

In terms of transfer learning, semantic gap means different meanings and purposes behind the same syntax between two or more domains. For example, suppose that we have a deep learning application to d …

Embedding is the process of representing data (from a source domain) in a new (or target) domain. Usually, the source domain is discrete, and the target domain is continuous. For example, embedding wo …

In a typical situation, for the emulation of physical environments, you need to define all physical rules and forces. In the "learned emulators", they use some machine learning techniques to learn tho …

A good example is the degree of freedom in Student's distribution: ‌ The degrees of freedom refers to the number of independent observations in a set of data. For example: When estimating a mean sc …

As there are different representation model for a KB, we can find different terminology in different domains. For example, in some AI articles, it's called ontology. …

You can know it better, if you know the concept of entropy: Information entropy is the average rate at which information is produced by a stochastic source of data. The information content (also call …

The automated planning is: Automated planning and scheduling, sometimes denoted as simply AI Planning,1 is a branch of artificial intelligence that concerns the realization of strategies or action …

As mentioned in the abstract of on of these papers, bad local minima is a suboptimal local minimum which means a local minimum that is near to a global minimum.

Near solution to your problem definition is reinforcement learning. You can define some reward using the objective function and define some possible state space for the machine and finally solve the p …