3 papers
cs.DB2026
LatentTune: Efficient Tuning of High Dimensional Database Parameters via Latent Representation Learning
Sein Kwon, Youngwan Jo, Seungyeon Choi +3
As data volumes continue to grow, optimizing database performance has become increasingly critical, making the implementation of effective tuning methods essential. Among various a…
cs.LG2025
Controllable 3D Molecular Generation for Structure-Based Drug Design Through Bayesian Flow Networks and Gradient Integration
Seungyeon Choi, Hwanhee Kim, Chihyun Park +7
Recent advances in Structure-based Drug Design (SBDD) have leveraged generative models for 3D molecular generation, predominantly evaluating model performance by binding affinity t…
cs.LG2024
SPIN: SE(3)-Invariant Physics Informed Network for Binding Affinity Prediction
Seungyeon Choi, Sangmin Seo, Sanghyun Park
Accurate prediction of protein-ligand binding affinity is crucial for rapid and efficient drug development. Recently, the importance of predicting binding affinity has led to incre…