research
∙
05/29/2019
Pre-training Graph Neural Networks
Many applications of machine learning in science and medicine, including...
share
research
∙
07/24/2018
Improved Training with Curriculum GANs
In this paper we introduce Curriculum GANs, a curriculum learning strate...
research
∙
07/24/2018
Weakly-Supervised Deep Learning of Heat Transport via Physics Informed Loss
In typical machine learning tasks and applications, it is necessary to o...
research
∙
06/07/2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
Generating novel graph structures that optimize given objectives while o...
research
∙
06/06/2017
Retrosynthetic reaction prediction using neural sequence-to-sequence models
We describe a fully data driven model that learns to perform a retrosynt...
research
∙
03/02/2017
MoleculeNet: A Benchmark for Molecular Machine Learning
Molecular machine learning has been maturing rapidly over the last few y...
research
∙
11/10/2016
Low Data Drug Discovery with One-shot Learning
Recent advances in machine learning have made significant contributions ...
research
∙
06/28/2016
Modeling Industrial ADMET Data with Multitask Networks
Deep learning methods such as multitask neural networks have recently be...
research
∙
06/06/2016
ROCS-Derived Features for Virtual Screening
Rapid overlay of chemical structures (ROCS) is a standard tool for the c...
research
∙
03/02/2016
Molecular Graph Convolutions: Moving Beyond Fingerprints
Molecular "fingerprints" encoding structural information are the workhor...
research
∙
02/06/2015