Our main contributions in this work are as follows: 1.

They do not study how the population loss decreases during the first stage.

Learning to detect and encode temporal regularities (TRs) in events is a prerequisite for human-like intelligence. These regularities should be formed from limited event samples and stored as easily retrievable representations.

A mixture of archeology and chemistry brings the aroma of mummification to museums. Breakthroughs, discoveries, and DIY tips sent six days a week. Visiting a museum could soon be a truly multisensory experience--smells included. Thanks to recent advances in the field of biomolecular archeology, scientists can now detect traces of molecular fingerprints on ancient artifacts. From these tiny particles, scientists can determine how the objects may have smelled .

In the mid-19th century, Bernhard Riemann conceived of a new way to think about mathematical spaces, providing the foundation for modern geometry and physics. Standing in the middle of a field, we can easily forget that we live on a round planet. We're so small in comparison to the Earth that from our point of view, it looks flat. The world is full of such shapes--ones that look flat to an ant living on them, even though they might have a more complicated global structure. Mathematicians call these shapes manifolds.

Modern deep learning models are highly overparameterized, resulting in large sets of parameter configurations that yield the same outputs. A significant portion of this redundancy is explained by symmetries in the parameter space--transformations that leave the network function unchanged. These symmetries shape the loss landscape and constrain learning dynamics, offering a new lens for understanding optimization, generalization, and model complexity that complements existing theory of deep learning. This survey provides an overview of parameter space symmetry. We summarize existing literature, uncover connections between symmetry and learning theory, and identify gaps and opportunities in this emerging field.