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Exploring Single-Cell Data with Deep Multitasking Neural Networks
Matthew Amodio
Krishnan Srinivasan
David van Dijk
Hussein Mohsen
Kristina Yim
Rebecca Muhle
Kevin R. Moon
Susan Kaech
Ryan …
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related paper
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|We present a class of efficient models called MobileNets for mobile and embedded vision applications. MobileNets are based on a streamlined architecture that uses depthw…
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## TL; DR
- ViT feature representations are *less hierarchical*.
- Early tr blocks learn both local and global dependencies provided with large enough dataset.
- Skip connections play much more i…
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Hi. It's a great project.
I want to use KAN in radar signal processing domain. As you know that the radar signal is complex number. When I create a dataset with complex data and try to train KAN it r…
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Hi! I am trying to extend the tutorials 3 and 4 to implement the Logistic Hazard loss in a Graph Neural Network for Graph-level prediction of survival. This is the[ example](https://docs.dgl.ai/tutori…
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If anyone could lend a hand porting this to python3/gtk3, I've made considerable progress here: https://github.com/smearle/gym-micropolis/tree/master/micropolis-4bots-gtk3, at the service of an OpenAI…
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[Deep prior-based sparse representation model for diffraction imaging: A plug-and-play method](https://www.sciencedirect.com/science/article/pii/S0165168419304037?via%3Dihub)
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This book provides a clear and detailed coverage of fundamental neural network architectures and learning rules.
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## Abstract
- Propose `Average Attention Network` module that serves as decoder for Transformer. Decoding speed improves x3~4 while preserving translation performance.
- Empirical evidence shown in …
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Hello Luca,
I try to run the program in my own computer, which is with GTX 2060 Super GPU. However it seems my 8GB memory is not enough because I always face OOM when allocating tensor with shape[6…