nds
Datasets
All datasets matching “nds”ndsTahoe-100M
Tahoe-100M
Tahoe-100M is a giga-scale single-cell perturbation atlas consisting of over 100 million transcriptomic profiles from
50 cancer cell lines exposed to 1,100 small-molecule perturbations. Generated using Vevo Therapeutics'
Mosaic high-throughput platform, Tahoe-100M enables deep, context-aware exploration of gene function, cellular states, and drug responses at unprecedented scale and resolution.
This dataset is designed to power the development of next-generation AI… See the full description on the dataset page: https://huggingface.co/datasets/nds029/Tahoe-100M.nDSMNDSC_TUT_2022
Cite this dataset Allen, C., and Bartok, A. P. NDSC TUT 2022. ColabFit, 2023. https://doi.org/10.60732/965983d1
This dataset has been curated and formatted for the ColabFit Exchange
This dataset is also available on the ColabFit Exchange:
https://materials.colabfit.org/id/DS_oqqwzogut1on_0
Visit the ColabFit Exchange to search additional datasets by author, description, element content and more.
https://materials.colabfit.org
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/colabfit/NDSC_TUT_2022.gvs_benchmarkGenerative View Stitching
Chonghyuk (ND) Song1
·
Michal Stary1
·
Boyuan Chen1
·
George Kopanas2
·
Vincent Sitzmann1
1MIT CSAIL, Scene Representation Group 2Runway ML
Paper | Website | GitHub
This is the official benchmark for the paper Generative View Stitching (GVS), which enables collision-free camera-guided video generation for predefined trajectories, and presents a non-autoregressive alternative to video length extrapolation.… See the full description on the dataset page: https://huggingface.co/datasets/ndsong/gvs_benchmark.wiki-nds
Dataset Card for "wiki-nds"
More Information needed
figDesigns in components, not screens. Sends you the one variant you were avoiding.
rioHappy at both ends of the request. Will not add a third framework.
scoutFinds the three projects solving your problem before you finish describing it.
junoFinds the lift, then tells you which cohort it actually came from.
runeReads the spec twice and the implementation three times. Usually finds the gap between them.