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- University of California, San FranciscoUS31 papers
- University of HoustonUS29 papers
- University of California, BerkeleyUS20 papers
- Space Telescope Science InstituteUS19 papers
- Lawrence Berkeley National LaboratoryUS18 papers
- Stanford UniversityUS17 papers
- Centre National de la Recherche ScientifiqueFR15 papers
- University of ArizonaUS14 papers
- The University of TokyoJP13 papers
- Jet Propulsion LaboratoryUS12 papers
- California Institute of TechnologyUS11 papers
- Princeton UniversityUS11 papers
15 papers · 1 filter
Targeted transfer learning to improve performance in small medical physics datasets
Miguel Romero, Yannet Interian, Timothy Solberg +1
The growing use of Machine Learning has produced significant advances in many fields. For image-based tasks, however, the use of deep learning remains challenging in small datasets…
ContamiNet: Detecting Contamination in Municipal Solid Waste
Khoury Ibrahim, Danielle A. Savage, Addie Schnirel +2
Leveraging over 30,000 images each with up to 89 labels collected by Recology---an integrated resource recovery company with both residential and commercial trash, recycling and co…
Precise Mass Determination of SPT-CL J2106-5844, the Most Massive Cluster at z>1
Jinhyub Kim, M. James Jee, Saul Perlmutter +5
We present a detailed high-resolution weak-lensing (WL) study of SPT-CL J2106-5844 at z=1.132, claimed to be the most massive system discovered at z > 1 in the South Pole Telescope…
MixModule: Mixed CNN Kernel Module for Medical Image Segmentation
Henry H. Yu, Xue Feng, Hao Sun +1
Convolutional neural networks (CNNs) have been successfully applied to medical image classification, segmentation, and related tasks. Among the many CNNs architectures, U-Net and i…
Spectral density, Levinson's theorem, and the extra term in the second virial coefficient for 1D delta-function potential
H. E. Camblong, A. Chakraborty, W. S. Daza +3
In contrast with the 3D result, the Beth-Uhlenbeck (BU) formula in 1D contains an extra -1/2 term. The origin of this -1/2 term is explained using a spectral density approach. To b…
MultiFiT: Efficient Multi-lingual Language Model Fine-tuning
Julian Martin Eisenschlos, Sebastian Ruder, Piotr Czapla +3
Pretrained language models are promising particularly for low-resource languages as they only require unlabelled data. However, training existing models requires huge amounts of co…