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1
Deep Convolutional Neural Network for Image Restoration and Synthesis
Deep Convolutional Neural Network for Image Restoration and Synthesis
Zhang, Yulun. | Northeastern University | 2021
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2
Leaving Their Mark: New Computational Methods Reveal Rich Latent Structure in Children's Human Figure Drawings
Leaving Their Mark: New Computational Methods Reveal Rich Latent Structure in Children's Human Figure Drawings
Jensen, Clint A. | The University of Wisconsin - Madison | 2025
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3
Broadening Our Understanding of Galaxy Mergers with Machine Learning, Simulations, and Observations
Broadening Our Understanding of Galaxy Mergers with Machine Learning, Simulations, and Observations
Schechter, Aimee L. | University of Colorado at Boulder | 2025
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4
Atmospheric Drivers of Extreme Antarctic Snowfall
Atmospheric Drivers of Extreme Antarctic Snowfall
Baiman, Rebecca Louise. | University of Colorado at Boulder | 2025
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5
Novel Optical Metasurfaces: From Machine-Learning Enabled Nanophotonic Design to Colloidal Metamaterials
Novel Optical Metasurfaces: From Machine-Learning Enabled Nanophotonic Design to Colloidal Metamaterials
Tanriover, Ibrahim. | Northwestern University | 2024
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6
Interplay Between Structure and Dynamics in Granular Materials and Twisted Strings
Interplay Between Structure and Dynamics in Granular Materials and Twisted Strings
Hanlan, Jesse. | University of Pennsylvania | 2024
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7
Measuring the 15O(α, γ)19Ne Reaction in Type I X-Ray Bursts Using 20Mg β-Decay
Measuring the 15O(α, γ)19Ne Reaction in Type I X-Ray Bursts Using 20Mg β-Decay
Wheeler, Tyler Markham. | Michigan State University | 2024
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8
Building Features in Visual Neural Networks
Building Features in Visual Neural Networks
Hamblin, Christopher. | Harvard University | 2024
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9
Optical-Based Microsecond Latency MHD Mode Tracking Through Deep Learning
Optical-Based Microsecond Latency MHD Mode Tracking Through Deep Learning
Wei, Yumou. | Columbia University | 2024
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10
Design Approaches for Lightweight Machine Learning Models- [electronic resource]
Design Approaches for Lightweight Machine Learning Models- [electronic resource]
Chang, Yangyang.Electrical Engineering. | University of Minnesota. | 2023
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