28 citations · 61 across the 5 of their papers we have counts for
8 papers
FinLoRA: Finetuning Quantized Financial Large Language Models Using Low-Rank Adaptation
Dannong Wang, Daniel Kim, Bo Jin +4
Finetuned large language models (LLMs) have shown remarkable performance in financial tasks, such as sentiment analysis and information retrieval. Due to privacy concerns, finetuni…
Protein-Mamba: Biological Mamba Models for Protein Function Prediction
Bohao Xu, Yingzhou Lu, Yoshitaka Inoue +3
Protein function prediction is a pivotal task in drug discovery, significantly impacting the development of effective and safe therapeutics. Traditional machine learning models oft…
Reinforced Genetic Algorithm for Structure-based Drug Design
Tianfan Fu, Wenhao Gao, Connor W. Coley +1
Structure-based drug design (SBDD) aims to discover drug candidates by finding molecules (ligands) that bind tightly to a disease-related protein (targets), which is the primary ap…
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design
Yuanqi Du, Tianfan Fu, Jimeng Sun +1
Molecule design is a fundamental problem in molecular science and has critical applications in a variety of areas, such as drug discovery, material science, etc. However, due to th…
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development
Kexin Huang, Tianfan Fu, Wenhao Gao +7
Therapeutics machine learning is an emerging field with incredible opportunities for innovatiaon and impact. However, advancement in this field requires formulation of meaningful l…
MolDesigner: Interactive Design of Efficacious Drugs with Deep Learning
Kexin Huang, Tianfan Fu, Dawood Khan +7
The efficacy of a drug depends on its binding affinity to the therapeutic target and pharmacokinetics. Deep learning (DL) has demonstrated remarkable progress in predicting drug ef…