activity
20212026
most citedA Survey on Deep Graph Generation: Methods and Applications

19 citations · 33 across the 10 of their papers we have counts for

collaborators
Showing cs.LGShow all

8 papers · 1 filter

cs.LG2026

MassSpecGym in the Wild: Uncovering and Correcting Evaluation Pitfalls in AI-Driven Molecule Discovery

Hongxuan Liu, Roman Bushuiev, Ivy Lightheart +12

Reliable benchmarking is critical for developing machine learning models for tandem mass spectrometry (MS/MS) based molecule discovery. Subtle issues in experimental design and mod…

cs.LG2026

SpecBridge: Bridging Mass Spectrometry and Molecular Representations via Cross-Modal Alignment

Yinkai Wang, Yan Zhou Chen, Xiaohui Chen +2

Small-molecule identification from tandem mass spectrometry (MS/MS) remains a bottleneck in untargeted settings where spectral libraries are incomplete. While deep learning offers…

cs.LG2025★ 1 cited

Large Language Model is Secretly a Protein Sequence Optimizer

Yinkai Wang, Jiaxing He, Yuanqi Du +5

We consider the protein sequence engineering problem, which aims to find protein sequences with high fitness levels, starting from a given wild-type sequence. Directed evolution ha…

cs.LG2025★ 3 cited

MADGEN: Mass-Spec attends to De Novo Molecular generation

Yinkai Wang, Xiaohui Chen, Liping Liu +1

The annotation (assigning structural chemical identities) of MS/MS spectra remains a significant challenge due to the enormous molecular diversity in biological samples and the lim…

cs.LG2025★ 1 cited

Graph Generative Pre-trained Transformer

Xiaohui Chen, Yinkai Wang, Jiaxing He +4

Graph generation is a critical task in numerous domains, including molecular design and social network analysis, due to its ability to model complex relationships and structured da…

cs.LG2022★ 5 cited

Multi-objective Deep Data Generation with Correlated Property Control

Shiyu Wang, Xiaojie Guo, Xuanyang Lin +11

Developing deep generative models has been an emerging field due to the ability to model and generate complex data for various purposes, such as image synthesis and molecular desig…

cs.LG2022★ 19 cited

A Survey on Deep Graph Generation: Methods and Applications

Yanqiao Zhu, Yuanqi Du, Yinkai Wang +4

Graphs are ubiquitous in encoding relational information of real-world objects in many domains. Graph generation, whose purpose is to generate new graphs from a distribution simila…

cs.LG2021★ 3 cited

Graph-based Ensemble Machine Learning for Student Performance Prediction

Yinkai Wang, Aowei Ding, Kaiyi Guan +2

Student performance prediction is a critical research problem to understand the students' needs, present proper learning opportunities/resources, and develop the teaching quality.…