Team, thank you for being such good ambassadors! 👏
#AIMNews #AIinMedicine
Team, thank you for being such good ambassadors! 👏
#AIMNews #AIinMedicine
2. Every podcast is turning into a YouTube show.
3. AI companies can't stop building TikTok clones.
Everything is becoming television.
I wrote about why that matters.
www.derekthompson.org/p/why-everyt...
2. Every podcast is turning into a YouTube show.
3. AI companies can't stop building TikTok clones.
Everything is becoming television.
I wrote about why that matters.
www.derekthompson.org/p/why-everyt...
MedEurIPS - Medical Imaging meets EurIPS
sites.google.com/view/medeurips
@aasaferagen.bsky.social
@benglocker.bsky.social @bernhardkainz.bsky.social
@danielrueckert.bsky.social
Ender Konukoglu
@stsaftaris.bsky.social
MedEurIPS - Medical Imaging meets EurIPS
sites.google.com/view/medeurips
@aasaferagen.bsky.social
@benglocker.bsky.social @bernhardkainz.bsky.social
@danielrueckert.bsky.social
Ender Konukoglu
@stsaftaris.bsky.social
At #EurIPS we are looking forward to welcoming presentations of all accepted NeurIPS papers, including a new “Salon des Refusés” track for papers which were rejected due to space constraints!
At #EurIPS we are looking forward to welcoming presentations of all accepted NeurIPS papers, including a new “Salon des Refusés” track for papers which were rejected due to space constraints!
Comprehensive visual-tabular representations for whole-heart assessment and beyond.
We introduce ViTa, a multi-view, multi-modal, multi-task model for cardiac MRI.
🧵 1/3
Comprehensive visual-tabular representations for whole-heart assessment and beyond.
We introduce ViTa, a multi-view, multi-modal, multi-task model for cardiac MRI.
🧵 1/3
🚩 Meet Dynamic, Automatic & Systematic (DAS) Red-Teaming from Jiazhen Pan and Bailiang Jian together with great collaborators! #AIMresearch
🧵 1/4
🚩 Meet Dynamic, Automatic & Systematic (DAS) Red-Teaming from Jiazhen Pan and Bailiang Jian together with great collaborators! #AIMresearch
🧵 1/4
1. Develop a new benchmark to show a weakness of SOTA models.
2. Create a new (or cleverly adapt an old) dataset to address this weakness.
3. Retrain a transformer.
1. Develop a new benchmark to show a weakness of SOTA models.
2. Create a new (or cleverly adapt an old) dataset to address this weakness.
3. Retrain a transformer.
arxiv.org/abs/2503.17024
Always happy to meet anyone working on representation learning or tabular DL and medical data
arxiv.org/abs/2503.17024
Always happy to meet anyone working on representation learning or tabular DL and medical data
The other side of the coin is the freedom to spontaneously take random days off in winter when it snows a lot to go ski!
The other side of the coin is the freedom to spontaneously take random days off in winter when it snows a lot to go ski!