💾 github.com/steineggerla...
📄 www.biorxiv.org/content/10.1...
🐍 available in bioconda
💾 github.com/steineggerla...
📄 www.biorxiv.org/content/10.1...
🐍 available in bioconda
doi.org/10.1038/s415...
doi.org/10.1038/s415...
linuxiac.com/pangolin-1-2...
#OpenSource #VPN
linuxiac.com/pangolin-1-2...
#OpenSource #VPN
Analysis of multi-condition single-cell data with latent embedding multivariate regression
www.nature.com/articles/s41...
Analysis of multi-condition single-cell data with latent embedding multivariate regression
www.nature.com/articles/s41...
giottosuite.com
Multi-slice/-modal registration
Joint cell type annotation⬅️ multiple segmentation
Integrated modalities-based Leiden clustering
@natmethods.nature.com 2025
www.nature.com/articles/s41...
giottosuite.com
Multi-slice/-modal registration
Joint cell type annotation⬅️ multiple segmentation
Integrated modalities-based Leiden clustering
@natmethods.nature.com 2025
www.nature.com/articles/s41...
- vou trocar de mongo pra cassandra (talvez scylla)
- posts ficarão em uma table mesmo, nada "table-per-user" muito menos multi-clustering *sinal da cruz*
- por enquanto vou me preocupar só com a timeline de "following" usando "fan in technique"
- vou trocar de mongo pra cassandra (talvez scylla)
- posts ficarão em uma table mesmo, nada "table-per-user" muito menos multi-clustering *sinal da cruz*
- por enquanto vou me preocupar só com a timeline de "following" usando "fan in technique"
Pangolin 1.23 introduces self-service HA and clustering, alongside CLI improvements, multi-admin support, and organization management updates.
#Linux
Pangolin 1.23 introduces self-service HA and clustering, alongside CLI improvements, multi-admin support, and organization management updates.
#Linux
(1) A parameter-efficient multi-head clustering projector using nested Matryoshka representations. It refines features into finer clusters, addressing semantic ambiguity, improving performance & memory efficiency
(1) A parameter-efficient multi-head clustering projector using nested Matryoshka representations. It refines features into finer clusters, addressing semantic ambiguity, improving performance & memory efficiency
Link Here ➡️ www.biorxiv.org/content/10.1...
Link Here ➡️ www.biorxiv.org/content/10.1...
Does this mean "literally off the charts", data sources getting cut off outright, or some kind of less horrid explanation? In any case, that's, uh. Quite the number to be clustering at.
Why are people so determined to get sick??
Does this mean "literally off the charts", data sources getting cut off outright, or some kind of less horrid explanation? In any case, that's, uh. Quite the number to be clustering at.
I was impressed both by the work MariaDB has done to make REPEATABLE READ more in line with the literature and also with Galera itself.
theconsensus.dev/p/2026/03/29...
I was impressed both by the work MariaDB has done to make REPEATABLE READ more in line with the literature and also with Galera itself.
theconsensus.dev/p/2026/03/29...
Google introduces a multi-vector training method that learns inherently clusterable representations, outperforming post-hoc clustering methods while reducing vector count.
📝 arxiv.org/abs/2505.11471
Google introduces a multi-vector training method that learns inherently clusterable representations, outperforming post-hoc clustering methods while reducing vector count.
📝 arxiv.org/abs/2505.11471