19 citations · 33 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
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…
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…
On Separate Normalization in Self-supervised Transformers
Xiaohui Chen, Yinkai Wang, Yuanqi Du +2
Self-supervised training methods for transformers have demonstrated remarkable performance across various domains. Previous transformer-based models, such as masked autoencoders (M…
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…
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…
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.…
Dataset Geography: Mapping Language Data to Language Users
Fahim Faisal, Yinkai Wang, Antonios Anastasopoulos
As language technologies become more ubiquitous, there are increasing efforts towards expanding the language diversity and coverage of natural language processing (NLP) systems. Ar…