This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...

In an interview with the Big Technology Podcast, Sam Altman seemed to struggle answering the tough questions about OpenAI’s path to profitability. At about the 36 minute mark the interviewer asked the ...

Proteins, essential molecular machines evolved over billions of years, perform critical life-sustaining functions encoded in their sequences and revealed through their 3D structures. Decoding their ...

Abstract: Exponential degradation modeling and its variants have been widely used to describe component or device degradation characteristics, such as exponential bearing degradation, and their ...

In this work, we offer a theoretical analysis of two modern optimization techniques for training large and complex models: (i) adaptive optimization algorithms, such as Adam, and (ii) the model ...

Corporate tax departments face a constant stream of challenges: regulatory uncertainty, mounting data demands, new tax policy changes, ongoing digital transformation. Whatever the specifics, every tax ...

Introduction: The SIR (Susceptible-Infected-Recovered) model is one of the simplest and most widely used frameworks for understanding epidemic outbreaks. Methods: A second-order dynamical system for ...

Closes 3813 and 3866 -- moves several new functions to the new interface (abs, square, all exp and log, isnan, isinf, isfinite) #3873 Successfully merging a pull request may close this issue. Closes ...

School of Pure and Applied Sciences, Mount Kenya University, Thika, Kenya. The Exponential distribution is a commonly used parametric model in survival analysis. It assumes that the time to event ...