Ester

California couldn’t catch a break from consecutive storms this winter. Heavy precipitation caused widespread flooding, while strong winds felled trees and damaged roads, power lines, and homes. The weeks of severe weather also turned fields into a muddy mess and disrupted work for the state’s many agricultural workers.The Mississippi River is Drying Out | Extreme EarthEster is one of those workers. She lives in Monterey County, which is along California’s central coastline and is known for grapes and wine production.…

Combining ancient Persian mythology with the impossible-to-explain bond between pets and humans, Untethered Sky by Fonda Lee captures pain, guilt, and revenge in a single tidy novella. As man-eating manticores stalk the countryside, giant rocs, their only known natural predator, are trained up in royal mews by ruhkers as the first line of defense against the mythological killers. Ester becomes one of these storied ruhkers, and Untethered Sky follows her journey as she trains her roc, Zahra.Lower Drought Conditions In…

Deriving optimal initial variance of weight matrices in neural network layers with ReLU activation functionInitialization techniques are one of the prerequisites for successfully training a deep learning architecture. Traditionally, weight initialization methods need to be compatible with the choice of an activation function as a mismatch can potentially affect training negatively.ReLU is one of the most commonly used activation functions in deep learning. Its properties make it a very convenient choice for scaling to…

Detailed derivation for finding optimal initial distributions of weight matrices in deep learning layers with tanh activation functionXavier Glorot's initialization is one of the most widely used methods for initializing weight matrices in neural networks. While in practice, it is straightforward to utilize in your deep learning setup, reflecting upon the mathematical reasoning behind this standard initialization technique can prove most beneficial. Additionally, a theoretical understanding of this method is often asked…