Training very deep neural networks requires a lot of memory. Using the tools in this package, developed jointly by Tim Salimans and Yaroslav Bulatov, you can trade off some of this memory usage with ...

Abstract: Deep neural networks often suffer from poor performance or even training failure due to the ill-conditioned problem, the vanishing/exploding gradient problem, and the saddle point problem.

Color gradient filament is fun stuff to play with. It lets you make 3D prints that slowly fade from one color to another along the Z-axis. [David Gozzard] wanted to do some printing with this effect, ...

† Department of Chemistry, Chemical Theory Center, and the Minnesota Supercomputing Institute, The University of Minnesota, Minneapolis, Minnesota 55455, United States ‡ Department of ...

Abstract: Large-scale multi-objective optimization problems (LSMOPs) pose challenges to existing optimizers since a set of well-converged and diverse solutions should be found in huge search spaces.

Objective metrics, intelligent test generation, and data-driven insights for LLM apps Ragas is your ultimate toolkit for evaluating and optimizing Large Language Model (LLM) applications. Say goodbye ...