![GTC Silicon Valley-2019: Generative Modeling for Wireless Network Performance Optimization | NVIDIA Developer GTC Silicon Valley-2019: Generative Modeling for Wireless Network Performance Optimization | NVIDIA Developer](https://developer.download.nvidia.com/video/gputechconf/gtc/2019/video/S9680/image.jpg)
GTC Silicon Valley-2019: Generative Modeling for Wireless Network Performance Optimization | NVIDIA Developer
![PDF] Optimizing distributions over molecular space. An Objective-Reinforced Generative Adversarial Network for Inverse-design Chemistry (ORGANIC) | Semantic Scholar PDF] Optimizing distributions over molecular space. An Objective-Reinforced Generative Adversarial Network for Inverse-design Chemistry (ORGANIC) | Semantic Scholar](https://d3i71xaburhd42.cloudfront.net/61c05d7cab4448a1585596cc7e00ab271c442c2e/3-Figure1-1.png)
PDF] Optimizing distributions over molecular space. An Objective-Reinforced Generative Adversarial Network for Inverse-design Chemistry (ORGANIC) | Semantic Scholar
![Mol-CycleGAN: a generative model for molecular optimization | Journal of Cheminformatics | Full Text Mol-CycleGAN: a generative model for molecular optimization | Journal of Cheminformatics | Full Text](https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13321-019-0404-1/MediaObjects/13321_2019_404_Figa_HTML.png)
Mol-CycleGAN: a generative model for molecular optimization | Journal of Cheminformatics | Full Text
![Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study | Journal of Cheminformatics | Full Text Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study | Journal of Cheminformatics | Full Text](https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs13321-021-00516-0/MediaObjects/13321_2021_516_Fig3_HTML.png)
Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study | Journal of Cheminformatics | Full Text
![Generative Deep Learning for Targeted Compound Design | Journal of Chemical Information and Modeling Generative Deep Learning for Targeted Compound Design | Journal of Chemical Information and Modeling](https://pubs.acs.org/cms/10.1021/acs.jcim.0c01496/asset/images/large/ci0c01496_0008.jpeg)
Generative Deep Learning for Targeted Compound Design | Journal of Chemical Information and Modeling
![A deep generative model trifecta: Three advances that work towards harnessing large-scale power - Microsoft Research A deep generative model trifecta: Three advances that work towards harnessing large-scale power - Microsoft Research](https://www.microsoft.com/en-us/research/uploads/prod/2020/04/table_dgm17474.png)
A deep generative model trifecta: Three advances that work towards harnessing large-scale power - Microsoft Research
![A deep generative model for molecule optimization via one fragment modification | Nature Machine Intelligence A deep generative model for molecule optimization via one fragment modification | Nature Machine Intelligence](https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs42256-021-00410-2/MediaObjects/42256_2021_410_Fig2_HTML.png)
A deep generative model for molecule optimization via one fragment modification | Nature Machine Intelligence
![Article: Deep generative models for ligand-based de novo design applied to multi-parametric optimization - Iktos Article: Deep generative models for ligand-based de novo design applied to multi-parametric optimization - Iktos](https://iktos.ai/wp-content/uploads/2022/03/1647269588422.jpeg)
Article: Deep generative models for ligand-based de novo design applied to multi-parametric optimization - Iktos
An illustration of different generative models discussed in the paper:... | Download High-Quality Scientific Diagram
![PDF] Benchmarking Deep Graph Generative Models for Optimizing New Drug Molecules for COVID-19 | Semantic Scholar PDF] Benchmarking Deep Graph Generative Models for Optimizing New Drug Molecules for COVID-19 | Semantic Scholar](https://d3i71xaburhd42.cloudfront.net/2e91f46d17e3acc19a68751c1068a3e7a728e2b0/2-Figure1-1.png)
PDF] Benchmarking Deep Graph Generative Models for Optimizing New Drug Molecules for COVID-19 | Semantic Scholar
![PDF] Benchmarking Deep Graph Generative Models for Optimizing New Drug Molecules for COVID-19 | Semantic Scholar PDF] Benchmarking Deep Graph Generative Models for Optimizing New Drug Molecules for COVID-19 | Semantic Scholar](https://d3i71xaburhd42.cloudfront.net/2e91f46d17e3acc19a68751c1068a3e7a728e2b0/5-Figure3-1.png)
PDF] Benchmarking Deep Graph Generative Models for Optimizing New Drug Molecules for COVID-19 | Semantic Scholar
Beyond generative models: superfast traversal, optimization, novelty, exploration and discovery (STONED) algorithm for molecules using SELFIES - Chemical Science (RSC Publishing)
![A deep generative model for molecule optimization via one fragment modification | Nature Machine Intelligence A deep generative model for molecule optimization via one fragment modification | Nature Machine Intelligence](https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs42256-021-00410-2/MediaObjects/42256_2021_410_Fig3_HTML.png)
A deep generative model for molecule optimization via one fragment modification | Nature Machine Intelligence
![A deep generative model for molecule optimization via one fragment modification | Nature Machine Intelligence A deep generative model for molecule optimization via one fragment modification | Nature Machine Intelligence](https://media.springernature.com/full/springer-static/image/art%3A10.1038%2Fs42256-021-00410-2/MediaObjects/42256_2021_410_Fig1_HTML.png)
A deep generative model for molecule optimization via one fragment modification | Nature Machine Intelligence
![Intermediate Layer Optimization for Inverse Problems using Deep Generative Models | Institute for Foundations of Machine Learning Intermediate Layer Optimization for Inverse Problems using Deep Generative Models | Institute for Foundations of Machine Learning](https://www.ifml.institute/sites/default/files/styles/max_1300x1300/public/2021-08/noisy.png?itok=c-UMHSTU)
Intermediate Layer Optimization for Inverse Problems using Deep Generative Models | Institute for Foundations of Machine Learning
![OptiMol: Optimization of Binding Affinities in Chemical Space for Drug Discovery | Journal of Chemical Information and Modeling OptiMol: Optimization of Binding Affinities in Chemical Space for Drug Discovery | Journal of Chemical Information and Modeling](https://pubs.acs.org/cms/10.1021/acs.jcim.0c00833/asset/images/medium/ci0c00833_0007.gif)