AZoOptics on MSN

End-to-end differentiable design of geometric waveguide displays

A novel differentiable approach optimizes geometric waveguide coatings, achieving substantial gains in light efficiency and uniformity for optical AR displays.
Nature

Turning a hobby into a job: How duplicated genes find new functions

Natural selection uses duplicated genes as raw material for functional innovation, co-opting their existing features to new functions. Understanding genetic innovation requires two questions to be ...
IEEE

BarrierNet: Differentiable Control Barrier Functions for Learning of Safe Robot Control

Abstract: Many safety-critical applications of neural networks, such as robotic control, require safety guarantees. This article introduces a method for ensuring the safety of learned models for ...
IEEE

Sampled-Data Consensus for Networked Euler-Lagrange Systems With Differentiable Scaling Functions

Abstract: This paper is concerned with the sampled-data consensus of networked Euler-Lagrange systems. The Euler-Lagrange system has enormous advantages in analyzing and designing dynamical systems.
Healthline

What You Need to Know About Liver Damage and Disease

Liver damage typically progresses through four stages — inflammation, fibrosis, cirrhosis, and end stage liver disease (ESLD) — with worsening scarring that reduces liver function. Liver failure can ...
GitHub

DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs

This is the implementation of DRUM, proposed in the following paper: DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs-- [arXive + appendix]. Ali Sadeghian, Mohammadreza Armandpour, ...
GitHub

TILP: Differentiable Learning of Temporal Logical Rules on Knowledge Graphs

This repository contains the code for the paper [ICLR 23] TILP: Differentiable Learning of Temporal Logical Rules on Knowledge Graphs. We propose TILP, the first differentiable framework for temporal ...