Silicon Valley's next risky self-optimization craze is unproven peptides

For many of these uses, the scientific backing is far weaker than that for GLP-1 drugs. Yet many users extrapolate from the ...
eLife

A differentiable model for optimizing the genetic drivers of synaptogenesis

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...
Semiconductor Engineering

AI Meets Device Modeling: Transforming Compact Modeling With Machine Learning

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...
IEEE

A Gradient-Based Optimization Algorithm for Optimal Control Problems with General Conformable Fractional Derivatives

Abstract: This paper presents an extended gradient-based optimization framework for optimal control problems governed by general conformable fractional derivatives (GCFDs), which unify various ...
IEEE

Prestack Seismic Inversion via Global Optimization With an Accurate Hessian Matrix and the Three-Variable Cauchy Distribution for Exact Zoeppritz Equations

Abstract: Prestack inversion is typically based on the Zoeppritz equation combined with gradient-based optimization of objective functions. To address the limitations of traditional gradient-based ...
Scientific Research Publishing

Ruder, S. (2017) An Overview of Gradient Descent Optimization Algorithms. arXiv: 1609.04747.

ABSTRACT: As drivers age, roadway conditions may become more challenging, particularly when normal aging is coupled with cognitive decline. Driving during lower visibility conditions, such as ...
marktechpost

This AI Paper Introduces Semantic Backpropagation and Gradient Descent: Advanced Methods for Optimizing Language-Based Agentic Systems

Language-based agentic systems represent a breakthrough in artificial intelligence, allowing for the automation of tasks such as question-answering, programming, and advanced problem-solving. These ...
marktechpost

LibMOON: A Gradient-Based Multiobjective Optimization Library for Large-Scale Machine Learning

Multiobjective optimization (MOO) is pivotal in machine learning, enabling researchers to balance multiple conflicting objectives in real-world applications. These applications include robotics, fair ...