Solving Bayesian inverse problems from the perspective of deep generative networks
Sign Up to like & getrecommendations! Published in 2019 at "Computational Mechanics"
DOI: 10.1007/s00466-019-01739-7
Abstract: Deep generative networks have achieved great success in high dimensional density approximation, especially for applications in natural images and language. In this paper, we investigate their approximation capability in capturing the posterior distribution in Bayesian… read more here.
Keywords: bayesian inverse; deep generative; inverse problems; solving bayesian ... See more keywords
A deep generative model for probabilistic energy forecasting in power systems: normalizing flows
Sign Up to like & getrecommendations! Published in 2022 at "Applied Energy"
DOI: 10.1016/j.apenergy.2021.117871
Abstract: Greater direct electrification of end-use sectors with a higher share of renewables is one of the pillars to power a carbon-neutral society by 2050. However, in contrast to conventional power plants, renewable energy is subject… read more here.
Keywords: power systems; energy; energy forecasting; normalizing flows ... See more keywords
Brain Encoding and Decoding in fMRI with Bidirectional Deep Generative Models
Sign Up to like & getrecommendations! Published in 2019 at "Engineering"
DOI: 10.1016/j.eng.2019.03.010
Abstract: Abstract Brain encoding and decoding via functional magnetic resonance imaging (fMRI) are two important aspects of visual perception neuroscience. Although previous researchers have made significant advances in brain encoding and decoding models, existing methods still… read more here.
Keywords: encoding decoding; brain encoding; deep generative; generative models ... See more keywords
Realistic generation of diffusion-weighted magnetic resonance brain images with deep generative models.
Sign Up to like & getrecommendations! Published in 2021 at "Magnetic resonance imaging"
DOI: 10.1016/j.mri.2021.06.001
Abstract: We study two state of the art deep generative networks, the Introspective Variational Autoencoder and the Style-Based Generative Adversarial Network, for the generation of new diffusion-weighted magnetic resonance images. We show that high quality, diverse… read more here.
Keywords: weighted magnetic; magnetic resonance; diffusion weighted; generative models ... See more keywords
History matching geological facies models based on ensemble smoother and deep generative models
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Petroleum Science and Engineering"
DOI: 10.1016/j.petrol.2019.02.037
Abstract: Abstract The current research trend in history matching is to consider more realistic reservoir models with complex geology. Hence, it is important to be able to update facies models during the solution. Although Kalman filter-based… read more here.
Keywords: facies models; history matching; deep generative; geological facies ... See more keywords
Advances and Challenges in De Novo Drug Design Using Three-Dimensional Deep Generative Models
Sign Up to like & getrecommendations! Published in 2022 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.2c00042
Abstract: A persistent goal for de novo drug design is to generate novel chemical compounds with desirable properties in a labor-, time-, and cost-efficient manner. Deep generative models provide alternative routes to this goal. Numerous model… read more here.
Keywords: generative models; drug design; novo drug; deep generative ... See more keywords
Deep Generative Models for 3D Linker Design
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Chemical Information and Modeling"
DOI: 10.1021/acs.jcim.9b01120
Abstract: Rational compound design remains a challenging problem for both computational methods and medicinal chemists. Computational generative methods have begun to show promising results for the design problem. However, they have not yet used the power… read more here.
Keywords: linker design; information; design; generative models ... See more keywords
Target-Focused Library Design by Pocket-Applied Computer Vision and Fragment Deep Generative Linking.
Sign Up to like & getrecommendations! Published in 2022 at "Journal of medicinal chemistry"
DOI: 10.1021/acs.jmedchem.2c00931
Abstract: We here describe a computational approach (POEM: Pocket Oriented Elaboration of Molecules) to drive the generation of target-focused libraries while taking advantage of all publicly available structural information on protein-ligand complexes. A collection of 31 384… read more here.
Keywords: target focused; pocket; computer vision; deep generative ... See more keywords
Deep Generative Modeling of Infrared Images Provides Signature of Cracking in Cross-Linked Polyethylene Pipe.
Sign Up to like & getrecommendations! Published in 2023 at "ACS applied materials & interfaces"
DOI: 10.1021/acsami.3c02564
Abstract: Hyperspectral infrared (IR) images contain a large amount of highly spatially resolved information about the chemical composition of a sample. However, the analysis of hyperspectral IR imaging data for complex heterogeneous systems can be challenging… read more here.
Keywords: generative modeling; cross linked; linked polyethylene; infrared images ... See more keywords
Derivatization Design of Synthetically Accessible Space for Optimization: In Silico Synthesis vs Deep Generative Design.
Sign Up to like & getrecommendations! Published in 2021 at "ACS medicinal chemistry letters"
DOI: 10.1021/acsmedchemlett.0c00540
Abstract: Molecular design is of utmost importance in lead optimization programs ultimately determining the fate of the project and the speed to reach preclinical stage. Newly designed lead analogues or new chemotypes must successfully address the… read more here.
Keywords: generative design; derivatization design; optimization; silico synthesis ... See more keywords
Deep generative neural network for accurate drug response imputation
Sign Up to like & getrecommendations! Published in 2021 at "Nature Communications"
DOI: 10.1038/s41467-021-21997-5
Abstract: Drug response differs substantially in cancer patients due to inter- and intra-tumor heterogeneity. Particularly, transcriptome context, especially tumor microenvironment, has been shown playing a significant role in shaping the actual treatment outcome. In this study,… read more here.
Keywords: generative neural; drug response; drug; neural network ... See more keywords