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Found 5 papers, 3 papers with code
Enhancing Molecular Property Prediction with Auxiliary Learning and Task-Specific Adaptation
Pretrained Graph Neural Networks have been widely adopted for various molecular property prediction tasks.
Precision Anti-Cancer Drug Selection via Neural Ranking
To address this, we developed neural ranking approaches that leverage large-scale drug response data across multiple cell lines from diverse cancer types.
Improving Compound Activity Classification via Deep Transfer and Representation Learning
In order to cope with limited training data for a target task, transfer learning for SAR modeling has been recently adopted to leverage information from data of related tasks.
A Pipeline to Understand Emerging Illness via Social Media Data Analysis: A Case Study on Breast Implant Illness
Our study provides the first analysis and derived knowledge of BII from social media using NLP techniques, and demonstrates the potential of using social media information to better understand similar emerging illnesses.
Adversarial Attacks and Defences: A Survey
Deep learning has emerged as a strong and efficient framework that can be applied to a broad spectrum of complex learning problems which were difficult to solve using the traditional machine learning techniques in the past.
