Add to ORKGIn recent years the scientific community has devoted much effort in the development of deep learning models for the generation of new molecules with desirable properties (i.e. drugs). This has produced many proposals in literature. However, a systematic comparison among the different VAE methods is still missing. For this reason, we propose an extensive testbed for the evaluation of generative models for drug discovery, and we present the results obtained by many of the models proposed in literature
The number of 'small' molecules that may be of interest to chemical biologists - chemical space - is...
Deep generative models have been an upsurge in the deep learning community since they were proposed....
While a multitude of deep generative models have recently emerged there exists no best practice for ...
In recent years the scientific community has devoted much effort in the development of deep learning...
Machine learning (ML) and Artificial Intelligence (AI) have had a renaissance during the last few ye...
© 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group. Introduction: Deep discrimin...
© 2020 American Chemical Society. All rights reserved. The discovery of functional molecules is an e...
Deep learning methods applied to drug discovery have been used to generate novel structures. In this...
Deep learning methods applied to drug discovery have been used to generate novel structures. In this...
Eine wichtige Aufgabe in der Pharmakologie, Toxikologie und in der Arz- neimittelentwicklung ist die...
It is more pressing than ever to reduce the time and costs for the development of lead compounds in ...
© 2017 American Chemical Society. Deep generative adversarial networks (GANs) are the emerging techn...
Machine learning methods have a long tradition in data-driven, computational drug discovery. Drug di...
Molecular design is a critical aspect of various scientific and industrial fields, where the propert...
One key challenge of drug discovery is the generation of molecules that can be synthesised in labora...
The number of 'small' molecules that may be of interest to chemical biologists - chemical space - is...
Deep generative models have been an upsurge in the deep learning community since they were proposed....
While a multitude of deep generative models have recently emerged there exists no best practice for ...
In recent years the scientific community has devoted much effort in the development of deep learning...
Machine learning (ML) and Artificial Intelligence (AI) have had a renaissance during the last few ye...
© 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group. Introduction: Deep discrimin...
© 2020 American Chemical Society. All rights reserved. The discovery of functional molecules is an e...
Deep learning methods applied to drug discovery have been used to generate novel structures. In this...
Deep learning methods applied to drug discovery have been used to generate novel structures. In this...
Eine wichtige Aufgabe in der Pharmakologie, Toxikologie und in der Arz- neimittelentwicklung ist die...
It is more pressing than ever to reduce the time and costs for the development of lead compounds in ...
© 2017 American Chemical Society. Deep generative adversarial networks (GANs) are the emerging techn...
Machine learning methods have a long tradition in data-driven, computational drug discovery. Drug di...
Molecular design is a critical aspect of various scientific and industrial fields, where the propert...
One key challenge of drug discovery is the generation of molecules that can be synthesised in labora...
The number of 'small' molecules that may be of interest to chemical biologists - chemical space - is...
Deep generative models have been an upsurge in the deep learning community since they were proposed....
While a multitude of deep generative models have recently emerged there exists no best practice for ...