Search Results for author:
Found 6 papers, 1 papers with code
Simple, Efficient and Scalable Structure-aware Adapter Boosts Protein Language Models
Fine-tuning Pre-trained protein language models (PLMs) has emerged as a prominent strategy for enhancing downstream prediction tasks, often outperforming traditional supervised learning approaches.
A Unified View on Neural Message Passing with Opinion Dynamics for Social Networks
Drawing inspiration from opinion dynamics in sociology, we propose ODNet, a novel message passing scheme incorporating bounded confidence, to refine the influence weight of local nodes for message propagation.
A general Temperature-Guided Language model to engineer enhanced Stability and Activity in Proteins
Designing protein mutants with high stability and activity is a critical yet challenging task in protein engineering.
Factor Decomposed Generative Adversarial Networks for Text-to-Image Synthesis
Prior works about text-to-image synthesis typically concatenated the sentence embedding with the noise vector, while the sentence embedding and the noise vector are two different factors, which control the different aspects of the generation.
A Ligand-and-structure Dual-driven Deep Learning Method for the Discovery of Highly Potent GnRH1R Antagonist to treat Uterine Diseases
Gonadotrophin-releasing hormone receptor (GnRH1R) is a promising therapeutic target for the treatment of uterine diseases.
T-Net: Deep Stacked Scale-Iteration Network for Image Dehazing
In order to reduce network parameters, the intra-stage recursive computation of ResNet is adopted in our Stack T-Net.
