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High-dimensional imaging using combinatorial channel multiplexing and deep learning - Nature Biotechnology
Abstract Understanding tissue structure and function requires tools that quantify the expression of multiple proteins at single-cell resolution while preserving spatial information. Current imaging technologies use a separate channel for each protein, limiting throughput and scalability. Here, we present combinatorial multiplexing (CombPlex), a combinatorial staining platform coupled with an algorithmic framework to exponentially increase the number of measured proteins.
Lumiere: A Space-Time Diffusion Model for Video Generation
Models citing this paper 0 No model linking this paper Cite arxiv.org/abs/2401.12945 in a model README.md to link it from this page. Datasets citing this paper 0 No dataset linking this paper Cite arxiv.org/abs/2401.12945 in a dataset README.md to link it from this page. No Space linking this paper Cite arxiv.org/abs/2401.12945 in a Space README.md to link it from this page. Collections including this paper 1
[2311.17009] Space-Time Diffusion Features for Zero-Shot Text-Driven Motion Transfer
arXiv:2311.17009 (cs) [Submitted on 28 Nov 2023 (v1), last revised 3 Dec 2023 (this version, v2)] Download PDF HTML (experimental) Comments: Subjects: Computer Vision and Pattern Recognition (cs.CV) Cite as: arXiv:2311.17009 [cs.CV] (or arXiv:2311.17009v2 [cs.CV] for this version) https://doi.org/10.48550/arXiv.2311.17009 Submission history From: Rafail Fridman [ view email] [v1] Tue, 28 Nov 2023 18:03:27 UTC (46,867 KB) [v2] Sun, 3 Dec 2023 12:30:05 UTC (46,867 KB) Bibliographic Tools...
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