20 citations · 23 across the 3 of their papers we have counts for
5 papers
Electronic Structure Guided Inverse Design Using Generative Models
Shuyi Jia, Panchapakesan Ganesh, Victor Fung
The electronic structure of a material fundamentally determines its underlying physical, and by extension, its functional properties. Consequently, the ability to identify or gener…
Pre-training Graph Neural Networks with Structural Fingerprints for Materials Discovery
Shuyi Jia, Shitij Govil, Manav Ramprasad +1
In recent years, pre-trained graph neural networks (GNNs) have been developed as general models which can be effectively fine-tuned for various potential downstream tasks in materi…
Representation-space diffusion models for generating periodic materials
Anshuman Sinha, Shuyi Jia, Victor Fung
Generative models hold the promise of significantly expediting the materials design process when compared to traditional human-guided or rule-based methodologies. However, effectiv…
LLMatDesign: Autonomous Materials Discovery with Large Language Models
Shuyi Jia, Chao Zhang, Victor Fung
Discovering new materials can have significant scientific and technological implications but remains a challenging problem today due to the enormity of the chemical space. Recent a…
On the Quantification of Image Reconstruction Uncertainty without Training Data
Sirui Bi, Victor Fung, Jiaxin Zhang
Computational imaging plays a pivotal role in determining hidden information from sparse measurements. A robust inverse solver is crucial to fully characterize the uncertainty indu…