18 citations · 38 across the 7 of their papers we have counts for
9 papers
Graph Forward Distribution Matching for Molecular Inverse Design
Yihan Zhu, Yuhan Liu, Brett Savoie +2
Achieving precise control over multiple properties without sacrificing chemical validity remains a central challenge in molecular inverse design. Existing reinforcement learning (R…
ChemDIRT: A Diversified Instruction, Representation, and Task Benchmark for Robust Chemistry-LLM Evaluation
Eric Inae, Tim Gunn, Chris Bond +1
The rapid advancement of large language models (LLMs) has led to increasing interest in their application to scientific domains such as chemistry. However, existing chemistry bench…
ADEPT-PolyGraphMT: Automated Molecular Simulation and Multi-Task Multi-Fidelity Machine Learning for Polymer Property Generation and Prediction
Sobin Alosious, Yuhan Liu, Jiaxin Xu +4
The discovery of polymers with targeted properties is challenged by the vast chemical design space and the limited availability of consistent, high-quality data across multiple pro…
Learning Repetition-Invariant Representations for Polymer Informatics
Yihan Zhu, Gang Liu, Eric Inae +2
Polymers are large macromolecules composed of repeating structural units known as monomers and are widely applied in fields such as energy storage, construction, medicine, and aero…
POINT: A Polymer Informatics Training and Testing Database
Jiaxin Xu, Gang Liu, Ruilan Guo +2
The advancement of polymer informatics has been significantly propelled by the integration of machine learning (ML) techniques, enabling the rapid prediction of polymer properties…
Superior Polymeric Gas Separation Membrane Designed by Explainable Graph Machine Learning
Jiaxin Xu, Agboola Suleiman, Gang Liu +5
Gas separation using polymer membranes promises to dramatically drive down the energy, carbon, and water intensity of traditional thermally driven separation, but developing the me…
Graph Diffusion Transformers for Multi-Conditional Molecular Generation
Gang Liu, Jiaxin Xu, Tengfei Luo +1
Inverse molecular design with diffusion models holds great potential for advancements in material and drug discovery. Despite success in unconditional molecular generation, integra…
Large Language Models on Graphs: A Comprehensive Survey
Bowen Jin, Gang Liu, Chi Han +3
Large language models (LLMs), such as GPT4 and LLaMA, are creating significant advancements in natural language processing, due to their strong text encoding/decoding ability and n…
Explaining Tree Model Decisions in Natural Language for Network Intrusion Detection
Noah Ziems, Gang Liu, John Flanagan +1
Network intrusion detection (NID) systems which leverage machine learning have been shown to have strong performance in practice when used to detect malicious network traffic. Deci…