GitHub

Quantum–Classical Hybrid Learning Framework for Molecular Property Prediction and Molecule Optimization in Drug Discovery

QuantumDrugAI is a hybrid quantum–classical deep learning framework designed for molecular property prediction and molecule optimization in AI-driven drug discovery applications. The framework ...
Wired

He Couldn’t Land a Job Interview. Was AI to Blame?

It was mid-October, peak leaf-peeping season in Hanover, New Hampshire, and Chad Markey was on a rare break between clinical rotations during his last year of medical school. He should have been ...
GitHub

High-performance optimization algorithms in Rust with Python bindings

Optimiz-rs provides blazingly fast, production-ready implementations of advanced optimization and statistical inference algorithms. Built with Rust for maximum performance and exposed to Python ...
IEEE

EvoPlace: Evolution of Optimization Algorithms for Global Placement via Large Language Models

Abstract: Optimization algorithms are widely employed to tackle complex problems, but designing them manually is often labor-intensive and requires significant expertise. Global placement is a ...
Forbes

The Quantum-AI Convergence: Why Hybrid Computing Will Define The Next Decade Of Innovation

The computing world stands at a historic inflection point. Compute demand for frontier AI is expected to grow 1,000 times over the next four to five years. Classical compute is hitting thermal, energy ...
Scientific Research Publishing

Ruder, S. (2016) An Overview of Gradient Descent Optimization Algorithms. arXiv Preprint.

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...