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Published in 2024 at "Medical Physics"
DOI: 10.1002/mp.17473
Abstract: The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this Special Report.
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Keywords:
grand challenge;
aapm grand;
modeling learning;
generative modeling ... See more keywords
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Published in 2024 at "Journal of Chemical Information and Modeling"
DOI: 10.1021/acs.jcim.3c01777
Abstract: In the early stages of drug development, large chemical libraries are typically screened to identify compounds of promising potency against the chosen targets. Often, however, the resulting hit compounds tend to have poor drug metabolism…
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Keywords:
inert compounds;
using generative;
initially inert;
potency ... See more keywords
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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…
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Keywords:
generative modeling;
cross linked;
linked polyethylene;
infrared images ... See more keywords
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Published in 2025 at "Psychological methods"
DOI: 10.1037/met0000674
Abstract: Theories of individual differences are foundational to psychological and brain sciences, yet they are traditionally developed and tested using superficial summaries of data (e.g., mean response times) that are disconnected from our otherwise rich conceptual…
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Keywords:
using generative;
reliability paradox;
generative models;
reliability ... See more keywords
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Published in 2025 at "NPJ Biofilms and Microbiomes"
DOI: 10.1038/s41522-025-00647-4
Abstract: Biofilms are critical for understanding environmental processes, developing biotechnology applications, and progressing in medical treatments of various infections. Nowadays, a key limiting factor for biofilm analysis is the difficulty in obtaining large datasets with fully…
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Keywords:
biofilm;
generative modeling;
biofilm images;
deep generative ... See more keywords
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Published in 2025 at "Npj Quantum Information"
DOI: 10.1038/s41534-025-01121-x
Abstract: Expectation Value Samplers (EVSs) are quantum generative models that can learn high-dimensional continuous distributions by measuring the expectation values of parameterized quantum circuits. However, these models can demand impractical quantum resources for good performance. We…
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Keywords:
expectation values;
variational quantum;
quantum generative;
generative modeling ... See more keywords
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Published in 2024 at "Nature Methods"
DOI: 10.1038/s41592-025-02808-x
Abstract: The field of single-cell genomics is now observing a marked increase in the prevalence of cohort-level studies that include hundreds of samples and feature complex designs. These data have tremendous potential for discovering how sample…
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Keywords:
cell genomics;
single cell;
level;
cell ... See more keywords
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Published in 2024 at "NeuroImage"
DOI: 10.1101/2024.04.02.24305197
Abstract: The circle of Willis (CoW) is a network of cerebral arteries with significant inter-individual anatomical variations. Deep learning has been used to characterize and quantify the status of the CoW in various applications for the…
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Keywords:
circle willis;
tof mra;
generative modeling;
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Published in 2024 at "Journal of Cheminformatics"
DOI: 10.1186/s13321-024-00829-w
Abstract: We present a user-friendly molecular generative pipeline called Pocket Crafter, specifically designed to facilitate hit finding activity in the drug discovery process. This workflow utilized a three-dimensional (3D) generative modeling method Pocket2Mol, for the de…
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Keywords:
drug;
drug discovery;
generative modeling;
pocket crafter ... See more keywords
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Published in 2025 at "PLOS Computational Biology"
DOI: 10.1371/journal.pcbi.1012092
Abstract: Measurements of neural responses to identically repeated experimental events often exhibit large amounts of variability. This noise is distinct from signal, operationally defined as the average expected response across repeated trials for each given event.…
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Keywords:
gsn;
noise;
disentangling signal;
generative modeling ... See more keywords
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Published in 2022 at "Frontiers in Human Neuroscience"
DOI: 10.3389/fnhum.2022.940842
Abstract: As a newly emerging field, connectomics has greatly advanced our understanding of the wiring diagram and organizational features of the human brain. Generative modeling-based connectome analysis, in particular, plays a vital role in deciphering the…
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Keywords:
magnetic resonance;
generative modeling;
mechanistic connectome;
functional magnetic ... See more keywords