6 papers
Quantum LEGO Learning: A Modular Design Principle for Hybrid Artificial Intelligence
Jun Qi, Chao-Han Huck Yang, Pin-Yu Chen +3
Hybrid quantum-classical learning models increasingly integrate neural networks with variational quantum circuits (VQCs) to exploit complementary inductive biases. However, many ex…
Epigenetic feedback reshapes dynamical landscapes in gene regulatory networks
Sascha H. Hauck, Sandip Saha, Narsis A. Kiani +1
Understanding how gene regulatory networks (GRNs) give rise to stable and dynamic cellular states remains a central challenge in theoretical biology, particularly when slow epigene…
Advancing the Scientific Method with Large Language Models: From Hypothesis to Discovery
Yanbo Zhang, Sumeer A. Khan, Adnan Mahmud +10
With recent Nobel Prizes recognising AI contributions to science, Large Language Models (LLMs) are transforming scientific research by enhancing productivity and reshaping the scie…
Leveraging Pre-Trained Neural Networks to Enhance Machine Learning with Variational Quantum Circuits
Jun Qi, Chao-Han Yang, Samuel Yen-Chi Chen +3
Quantum Machine Learning (QML) offers tremendous potential but is currently limited by the availability of qubits. We introduce an innovative approach that utilizes pre-trained neu…
T- Hop: A framework for studying the importance path information in molecular graphs for chemical property prediction
Abdulrahman Ibraheem, Narsis Kiani, Jesper Tegner
This paper studies the usefulness of incorporating path information in predicting chemical properties from molecular graphs, in the domain of QSAR (Quantitative Structure-Activity…
A Decomposition Method for Global Evaluation of Shannon Entropy and Local Estimations of Algorithmic Complexity
Hector Zenil, Santiago Hernández-Orozco, Narsis A. Kiani +2
We investigate the properties of a Block Decomposition Method (BDM), which extends the power of a Coding Theorem Method (CTM) that approximates local estimations of algorithmic com…