From Germany:
Transcriptome analysis of classical blood cells reveals down-regulation of proinflammatory genes in the classical monocytes of Long-COVID patients
www.frontiersin.org/journals/imm...
Screenshot from latest Science for ME weekly update
#LongCovid #PASC
Transcriptome analysis of classical blood cells reveals down-regulation of proinflammatory genes in the classical monocytes of Long-COVID patients
www.frontiersin.org/journals/imm...
Screenshot from latest Science for ME weekly update
#LongCovid #PASC
November 11, 2025 at 1:41 AM
From Germany:
Transcriptome analysis of classical blood cells reveals down-regulation of proinflammatory genes in the classical monocytes of Long-COVID patients
www.frontiersin.org/journals/imm...
Screenshot from latest Science for ME weekly update
#LongCovid #PASC
Transcriptome analysis of classical blood cells reveals down-regulation of proinflammatory genes in the classical monocytes of Long-COVID patients
www.frontiersin.org/journals/imm...
Screenshot from latest Science for ME weekly update
#LongCovid #PASC
Detecting FRB by DANCE: a method based on DEnsity ANalysis and Cluster Extraction. Mao Yuan et. al. https://arxiv.org/abs/2511.04966
November 11, 2025 at 12:49 AM
Detecting FRB by DANCE: a method based on DEnsity ANalysis and Cluster Extraction. Mao Yuan et. al. https://arxiv.org/abs/2511.04966
Btw I see these examples as dragons on the edge of the map - I think clustering features together is a useful strategy until we can isolate some features as causal. It is also crucial to be transparent about the status of the concepts we invoke both in research and clinical practice.....
November 10, 2025 at 9:56 PM
Btw I see these examples as dragons on the edge of the map - I think clustering features together is a useful strategy until we can isolate some features as causal. It is also crucial to be transparent about the status of the concepts we invoke both in research and clinical practice.....
#AskingForMe because I'm ruining my life (figuratively). I'm ISO a storage clustering + container tech for play in a #HomeLab. Thus begins a 🧵of pain and the things I've tried.
November 10, 2025 at 5:14 PM
#AskingForMe because I'm ruining my life (figuratively). I'm ISO a storage clustering + container tech for play in a #HomeLab. Thus begins a 🧵of pain and the things I've tried.
🧵
11/13 - Sample spectral clustering for land use classification using Sentinel-2 L2 data - EOPF
11/14 - Developing a Scalable Online Ecology Course with 4DEE - ESA - esa.zoom.us/meeting/register/ITcQk2NRRKmM47xOne1n8A#/registration
11/13 - Sample spectral clustering for land use classification using Sentinel-2 L2 data - EOPF
11/14 - Developing a Scalable Online Ecology Course with 4DEE - ESA - esa.zoom.us/meeting/register/ITcQk2NRRKmM47xOne1n8A#/registration
Welcome! You are invited to join a webinar: Sample spectral clustering for land use classification using Sentinel-2 L2 data. After registering, you will receive a confirmation email about joining the ...
This webinar showcases results from the EOPF Hackathon held during BiDS25, focusing on innovative methods for processing Sentinel data in Zarr format. A featured hackathon team presents their project,...
us02web.zoom.us
November 10, 2025 at 4:48 PM
🧵
11/13 - Sample spectral clustering for land use classification using Sentinel-2 L2 data - EOPF
11/14 - Developing a Scalable Online Ecology Course with 4DEE - ESA - esa.zoom.us/meeting/register/ITcQk2NRRKmM47xOne1n8A#/registration
11/13 - Sample spectral clustering for land use classification using Sentinel-2 L2 data - EOPF
11/14 - Developing a Scalable Online Ecology Course with 4DEE - ESA - esa.zoom.us/meeting/register/ITcQk2NRRKmM47xOne1n8A#/registration
link 📈🤖
Clustering in Networks with Time-varying Nodal Attributes (Kei, Padilla, Killick et al) This manuscript studies nodal clustering in graphs having a time series at each node. The framework includes priors for low-dimensional representations and a decoder that bridges the latent representat
Clustering in Networks with Time-varying Nodal Attributes (Kei, Padilla, Killick et al) This manuscript studies nodal clustering in graphs having a time series at each node. The framework includes priors for low-dimensional representations and a decoder that bridges the latent representat
November 10, 2025 at 4:18 PM
link 📈🤖
Clustering in Networks with Time-varying Nodal Attributes (Kei, Padilla, Killick et al) This manuscript studies nodal clustering in graphs having a time series at each node. The framework includes priors for low-dimensional representations and a decoder that bridges the latent representat
Clustering in Networks with Time-varying Nodal Attributes (Kei, Padilla, Killick et al) This manuscript studies nodal clustering in graphs having a time series at each node. The framework includes priors for low-dimensional representations and a decoder that bridges the latent representat
I will assume @neurovagrant is back from PTO, so here's today's "Depress Ian" report (some details are in alt-text).
I caught up with an odd bump poking at Apache Superset (semi-popular data analysis thing) back in mid-October.
Pulled out my new clustering […]
[Original post on mastodon.social]
I caught up with an odd bump poking at Apache Superset (semi-popular data analysis thing) back in mid-October.
Pulled out my new clustering […]
[Original post on mastodon.social]
November 10, 2025 at 3:47 PM
I will assume @neurovagrant is back from PTO, so here's today's "Depress Ian" report (some details are in alt-text).
I caught up with an odd bump poking at Apache Superset (semi-popular data analysis thing) back in mid-October.
Pulled out my new clustering […]
[Original post on mastodon.social]
I caught up with an odd bump poking at Apache Superset (semi-popular data analysis thing) back in mid-October.
Pulled out my new clustering […]
[Original post on mastodon.social]
I posted two "new" chapters for my online book:
1. Coresets for clustering: sarielhp.org/book/chapter...
2. No dimensional geometric algorithms: sarielhp.org/book/chapter...
The webpage of the book is here: sarielhp.org/book/
1. Coresets for clustering: sarielhp.org/book/chapter...
2. No dimensional geometric algorithms: sarielhp.org/book/chapter...
The webpage of the book is here: sarielhp.org/book/
sarielhp.org
November 10, 2025 at 3:46 PM
I posted two "new" chapters for my online book:
1. Coresets for clustering: sarielhp.org/book/chapter...
2. No dimensional geometric algorithms: sarielhp.org/book/chapter...
The webpage of the book is here: sarielhp.org/book/
1. Coresets for clustering: sarielhp.org/book/chapter...
2. No dimensional geometric algorithms: sarielhp.org/book/chapter...
The webpage of the book is here: sarielhp.org/book/
🚨⚖️📚Decoupling escalates: China bans U.S. AI chips in state data centers, channeling spend to Huawei/Cambricon and clustering local GPUs to scale. Cheaper power and vast renewables tilt the energy war. De-dollarization quickens as RMB trade grows; gold now tops Treasuries. DC debt & MBS risks loom.
China Just Banned ALL U.S. Chips As Russia-China Eliminates ALL USD Payments In Trade
YouTube video by Sean Foo
youtu.be
November 10, 2025 at 2:37 PM
🚨⚖️📚Decoupling escalates: China bans U.S. AI chips in state data centers, channeling spend to Huawei/Cambricon and clustering local GPUs to scale. Cheaper power and vast renewables tilt the energy war. De-dollarization quickens as RMB trade grows; gold now tops Treasuries. DC debt & MBS risks loom.
New paper in Ticks and Tick-borne Diseases using @gbif.org mediated data:
Spatial distribution and clustering of medically important tick species in Illinois: Implications for tick-borne disease risk 🇺🇸
#CiteTheDOI: ❌
https://doi.org/10.1016/j.ttbdis.2025.102533
Spatial distribution and clustering of medically important tick species in Illinois: Implications for tick-borne disease risk 🇺🇸
#CiteTheDOI: ❌
https://doi.org/10.1016/j.ttbdis.2025.102533
November 10, 2025 at 12:35 PM
New paper in Ticks and Tick-borne Diseases using @gbif.org mediated data:
Spatial distribution and clustering of medically important tick species in Illinois: Implications for tick-borne disease risk 🇺🇸
#CiteTheDOI: ❌
https://doi.org/10.1016/j.ttbdis.2025.102533
Spatial distribution and clustering of medically important tick species in Illinois: Implications for tick-borne disease risk 🇺🇸
#CiteTheDOI: ❌
https://doi.org/10.1016/j.ttbdis.2025.102533
After a long review process, our locomotor clustering manuscript has finally been accepted!
Keep an eye for a summary thread once it's out!
Keep an eye for a summary thread once it's out!
November 10, 2025 at 12:26 PM
After a long review process, our locomotor clustering manuscript has finally been accepted!
Keep an eye for a summary thread once it's out!
Keep an eye for a summary thread once it's out!
Male Nomia bees clustering
(Lipotiches australica)
#MacroMonday
#photography #macro #insects #diptera #bees #Lipotriches #EastCoastKin
(Lipotiches australica)
#MacroMonday
#photography #macro #insects #diptera #bees #Lipotriches #EastCoastKin
November 10, 2025 at 11:26 AM
Male Nomia bees clustering
(Lipotiches australica)
#MacroMonday
#photography #macro #insects #diptera #bees #Lipotriches #EastCoastKin
(Lipotiches australica)
#MacroMonday
#photography #macro #insects #diptera #bees #Lipotriches #EastCoastKin
The future of fraud detection lies in advanced clustering algorithms like DBSCAN. DBSCAN's ability to handle clusters of varying densities makes it a powerful tool for anomaly detection.
November 10, 2025 at 9:55 AM
The future of fraud detection lies in advanced clustering algorithms like DBSCAN. DBSCAN's ability to handle clusters of varying densities makes it a powerful tool for anomaly detection.
ICCS presented “Robust Federated Learning under Adversarial Attacks via Loss-Based Client Clustering” at WAFL @ ECML-PKDD 2025 (Porto, Portugal) — a loss-based clustering approach enabling robust FL even under various malicious attacks.
November 10, 2025 at 9:00 AM
ICCS presented “Robust Federated Learning under Adversarial Attacks via Loss-Based Client Clustering” at WAFL @ ECML-PKDD 2025 (Porto, Portugal) — a loss-based clustering approach enabling robust FL even under various malicious attacks.
Jingqing Wang, Jiaxing Shang, Rong Xu, Fei Hao, Tianjin Huang, Geyong Min
SARC: Sentiment-Augmented Deep Role Clustering for Fake News Detection
https://arxiv.org/abs/2511.04692
SARC: Sentiment-Augmented Deep Role Clustering for Fake News Detection
https://arxiv.org/abs/2511.04692
November 10, 2025 at 8:05 AM
Jingqing Wang, Jiaxing Shang, Rong Xu, Fei Hao, Tianjin Huang, Geyong Min
SARC: Sentiment-Augmented Deep Role Clustering for Fake News Detection
https://arxiv.org/abs/2511.04692
SARC: Sentiment-Augmented Deep Role Clustering for Fake News Detection
https://arxiv.org/abs/2511.04692
Shubhayan Pan, Saptarshi Chakraborty, Debolina Paul, Kushal Bose, Swagatam Das: A New Framework for Convex Clustering in Kernel Spaces: Finite Sample Bounds, Consistency and Performance Insights https://arxiv.org/abs/2511.05159 https://arxiv.org/pdf/2511.05159 https://arxiv.org/html/2511.05159
November 10, 2025 at 6:53 AM
Shubhayan Pan, Saptarshi Chakraborty, Debolina Paul, Kushal Bose, Swagatam Das: A New Framework for Convex Clustering in Kernel Spaces: Finite Sample Bounds, Consistency and Performance Insights https://arxiv.org/abs/2511.05159 https://arxiv.org/pdf/2511.05159 https://arxiv.org/html/2511.05159
Yik Lun Kei, Oscar Hernan Madrid Padilla, Rebecca Killick, James Wilson, Xi Chen, Robert Lund: Clustering in Networks with Time-varying Nodal Attributes https://arxiv.org/abs/2511.04859 https://arxiv.org/pdf/2511.04859 https://arxiv.org/html/2511.04859
November 10, 2025 at 6:53 AM
Yik Lun Kei, Oscar Hernan Madrid Padilla, Rebecca Killick, James Wilson, Xi Chen, Robert Lund: Clustering in Networks with Time-varying Nodal Attributes https://arxiv.org/abs/2511.04859 https://arxiv.org/pdf/2511.04859 https://arxiv.org/html/2511.04859
Jingqing Wang, Jiaxing Shang, Rong Xu, Fei Hao, Tianjin Huang, Geyong Min: SARC: Sentiment-Augmented Deep Role Clustering for Fake News Detection https://arxiv.org/abs/2511.04692 https://arxiv.org/pdf/2511.04692 https://arxiv.org/html/2511.04692
November 10, 2025 at 6:29 AM
Jingqing Wang, Jiaxing Shang, Rong Xu, Fei Hao, Tianjin Huang, Geyong Min: SARC: Sentiment-Augmented Deep Role Clustering for Fake News Detection https://arxiv.org/abs/2511.04692 https://arxiv.org/pdf/2511.04692 https://arxiv.org/html/2511.04692
Shubhayan Pan, Saptarshi Chakraborty, Debolina Paul, Kushal Bose, Swagatam Das
A New Framework for Convex Clustering in Kernel Spaces: Finite Sample Bounds, Consistency and Performance Insights
https://arxiv.org/abs/2511.05159
A New Framework for Convex Clustering in Kernel Spaces: Finite Sample Bounds, Consistency and Performance Insights
https://arxiv.org/abs/2511.05159
November 10, 2025 at 5:38 AM
Shubhayan Pan, Saptarshi Chakraborty, Debolina Paul, Kushal Bose, Swagatam Das
A New Framework for Convex Clustering in Kernel Spaces: Finite Sample Bounds, Consistency and Performance Insights
https://arxiv.org/abs/2511.05159
A New Framework for Convex Clustering in Kernel Spaces: Finite Sample Bounds, Consistency and Performance Insights
https://arxiv.org/abs/2511.05159
Yik Lun Kei, Oscar Hernan Madrid Padilla, Rebecca Killick, James Wilson, Xi Chen, Robert Lund
Clustering in Networks with Time-varying Nodal Attributes
https://arxiv.org/abs/2511.04859
Clustering in Networks with Time-varying Nodal Attributes
https://arxiv.org/abs/2511.04859
November 10, 2025 at 5:13 AM
Yik Lun Kei, Oscar Hernan Madrid Padilla, Rebecca Killick, James Wilson, Xi Chen, Robert Lund
Clustering in Networks with Time-varying Nodal Attributes
https://arxiv.org/abs/2511.04859
Clustering in Networks with Time-varying Nodal Attributes
https://arxiv.org/abs/2511.04859
Separate the Wheat from the Chaff: Winnowing Down Divergent Views in Retrieval Augmented Generation
Proposes a framework that systematically filters noisy documents through query-aware clustering and multi-agent iterative refinement.
📝 arxiv.org/abs/2511.04700
👨🏽💻 github.com/SongW-SW/Win...
Proposes a framework that systematically filters noisy documents through query-aware clustering and multi-agent iterative refinement.
📝 arxiv.org/abs/2511.04700
👨🏽💻 github.com/SongW-SW/Win...
Separate the Wheat from the Chaff: Winnowing Down Divergent Views in Retrieval Augmented Generation
Retrieval-augmented generation (RAG) enhances large language models (LLMs) by integrating external knowledge sources to address their limitations in accessing up-to-date or specialized information. A ...
arxiv.org
November 10, 2025 at 3:23 AM
Separate the Wheat from the Chaff: Winnowing Down Divergent Views in Retrieval Augmented Generation
Proposes a framework that systematically filters noisy documents through query-aware clustering and multi-agent iterative refinement.
📝 arxiv.org/abs/2511.04700
👨🏽💻 github.com/SongW-SW/Win...
Proposes a framework that systematically filters noisy documents through query-aware clustering and multi-agent iterative refinement.
📝 arxiv.org/abs/2511.04700
👨🏽💻 github.com/SongW-SW/Win...
Clustering #Countries on #Development Indicators Reveals Structure Relevant for #H5N1 #Mortality Analysis, etidiohnew.blogspot.com/2025/11/clus...
Clustering #Countries on #Development Indicators Reveals Structure Relevant for #H5N1 #Mortality Analysis
etidiohnew.blogspot.com
November 9, 2025 at 8:22 PM
Clustering #Countries on #Development Indicators Reveals Structure Relevant for #H5N1 #Mortality Analysis, etidiohnew.blogspot.com/2025/11/clus...
Clustering Countries on Development Indicators Reveals Structure Relevant for H5N1 Mortality Analysis https://www.medrxiv.org/content/10.1101/2025.11.08.25339808v1
November 9, 2025 at 6:43 PM
Clustering Countries on Development Indicators Reveals Structure Relevant for H5N1 Mortality Analysis https://www.medrxiv.org/content/10.1101/2025.11.08.25339808v1
Why so little age clustering? Likely that high site fidelity among survivors coupled with high mortality & immigration → frequent territory turnover. This weakens any stable link between age and quality and erodes repeatable spatial age structure 6/n
November 9, 2025 at 5:01 PM
Why so little age clustering? Likely that high site fidelity among survivors coupled with high mortality & immigration → frequent territory turnover. This weakens any stable link between age and quality and erodes repeatable spatial age structure 6/n
We found very little consistent clustering of age in space. In contrast, habitat features were strongly spatially structured, and reproductive output showed modest spatial patterning. Spatial age patterns also shift from year to year 5/n
November 9, 2025 at 5:01 PM
We found very little consistent clustering of age in space. In contrast, habitat features were strongly spatially structured, and reproductive output showed modest spatial patterning. Spatial age patterns also shift from year to year 5/n