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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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Hello there,
I am writing a module based on ANI2x that requires AEVs and have been trying to use a forward hook on the ANI2x AEVComputer to avoid duplicating the calculation. While this works perfe…
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Published: https://doi.org/10.1093/nar/gkx681
Preprint: https://doi.org/10.1101/129759
> While only recently developed, the ability to profile expression data in single cells (scRNA-Seq) has alr…
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Abstract: We present Compositional Attention Networks, a novel fully differentiable neural network architecture, designed to facilitate explicit and expressive reasoning. While many types of neural ne…
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https://doi.org/10.1021/acs.jcim.8b00670
> Predicting the outcome of biological assays based on high-throughput imaging data is a highly promising task in drug discovery since it can tremendously i…
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### Is there an existing issue for this?
- [X] I have searched the existing issues
### Feature Description
- Deep learning techniques, particularly convolutional neural networks (CNNs), are extensi…
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Hello! While fitting VQC on a (3599, 20) training dataset I faced the following exception:
`MemoryError: Unable to allocate 1.64 GiB for an array with shape (1048576,) and data type
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### Deep Learning Simplified Repository (Proposing new issue)
:red_circle: **Project Title** : Facial Skin Diseases Classification using DL
:red_circle: **Aim** : The aim of this project is to class…
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https://arxiv.org/pdf/1611.01578.pdf
Neural networks are powerful and flexible models that work well for many difficult learning tasks in image, speech and natural language understanding. Despite t…
leo-p updated
7 years ago
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Hi,
I found the list missed some recent papers:
>[Multimodal Integration] [2022 Nature Biotechnology] Multi-omics single-cell data integration and regulatory inference with graph-linked embedding
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