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Linjiang Chen

4 accepted papers

2026

From Sorting Algorithms to Scalable Kernels: Bayesian Optimization in High-Dimensional Permutation Spaces

ICLR 2026poster

Bayesian Optimization (BO) is a powerful tool for black-box optimization, but its application to high-dimensional permutation spaces is severely limited by the challenge of defining scalable representations. The current state-of-the-art BO approach for permutation spaces relies on an exhaustive $\Om…

Cited by 2SourceScholar
2026

MSAnchor: De Novo Molecular Generation from Mass Spectrometry Data with Anchor-Extended Molecular Scaffolds

AAAI 2026technical

Tandem mass spectrometry (MS/MS) is a critical tool for identifying molecular structures. By efficiently separating molecular fragments based on their mass-to-charge (m/z) ratios, it facilitates molecular generation and subsequent scientific discoveries. However, de novo molecular generation from MS

Cited by 0SourcePDFScholar
2025

Deciphering the Extremes: A Novel Approach for Pathological Long-tailed Recognition in Scientific Discovery

NeurIPS 2025spotlight

Scientific discovery across diverse fields increasingly grapples with datasets exhibiting pathological long-tailed distributions: a few common phenomena overshadow a multitude of rare yet scientifically critical instances. Unlike standard benchmarks, these scientific datasets often feature extreme i…

Cited by 0SourceScholar
2025

ModuLM: Enabling Modular and Multimodal Molecular Relational Learning with Large Language Models

NeurIPS 2025poster

Molecular Relational Learning (MRL) aims to understand interactions between molecular pairs, playing a critical role in advancing biochemical research. With the recent development of large language models (LLMs), a growing number of studies have explored the integration of MRL with LLMs and achieved…

Cited by 0SourceScholar