Jeremias Sulam
@jsulam.bsky.social
Assistant Prof. @ JHU 🇦🇷🇺🇸 Mathematics of Data & Biomedical Data Science
jsulam.github.io
jsulam.github.io
Check this out 📢 Score-based diffusion models are powerful—but slow to sample. Could there be something better? Drop the scores, use proximals instead!
We present Proximal Diffusion Models, providing a faster alternative both in theory* and practice. Here’s how it works 🧵(1/n)
We present Proximal Diffusion Models, providing a faster alternative both in theory* and practice. Here’s how it works 🧵(1/n)
July 22, 2025 at 7:25 PM
Check this out 📢 Score-based diffusion models are powerful—but slow to sample. Could there be something better? Drop the scores, use proximals instead!
We present Proximal Diffusion Models, providing a faster alternative both in theory* and practice. Here’s how it works 🧵(1/n)
We present Proximal Diffusion Models, providing a faster alternative both in theory* and practice. Here’s how it works 🧵(1/n)
Awesome to see our cover in @cp-patterns.bsky.social finally out! And kudos go to Zhenzhen Wang for her massive work on biomarker discovery for breast cancer
www.cell.com/patterns/ful...
www.cell.com/patterns/ful...
March 14, 2025 at 4:09 PM
Awesome to see our cover in @cp-patterns.bsky.social finally out! And kudos go to Zhenzhen Wang for her massive work on biomarker discovery for breast cancer
www.cell.com/patterns/ful...
www.cell.com/patterns/ful...
Today, on #WomenInScience day, this paper on biomarker discovery for breast cancer, by my amazing student Zhenzhen, has just appeared in @cp-patterns.bsky.social
🎉 Her work shows how to construct fully interpretable biomarkers employing bi-level graph learning! @jhu.edu @hopkinsdsai.bsky.social
🎉 Her work shows how to construct fully interpretable biomarkers employing bi-level graph learning! @jhu.edu @hopkinsdsai.bsky.social
February 12, 2025 at 2:30 AM
Today, on #WomenInScience day, this paper on biomarker discovery for breast cancer, by my amazing student Zhenzhen, has just appeared in @cp-patterns.bsky.social
🎉 Her work shows how to construct fully interpretable biomarkers employing bi-level graph learning! @jhu.edu @hopkinsdsai.bsky.social
🎉 Her work shows how to construct fully interpretable biomarkers employing bi-level graph learning! @jhu.edu @hopkinsdsai.bsky.social
Nice write-up by @JHUCompSci about @JacopoTeneggi's work. Puch-line: interpretability of opaque ML models can be posed as hypothesis tests, for which online (efficient) testing procedures can be derived! www.cs.jhu.edu/news/wanna-b...
Wanna bet? Testing conceptual importance for more explainable AI
Johns Hopkins researchers used betting strategies to help clarify AI models’ decision-making processes.
www.cs.jhu.edu
December 13, 2024 at 5:47 PM
Nice write-up by @JHUCompSci about @JacopoTeneggi's work. Puch-line: interpretability of opaque ML models can be posed as hypothesis tests, for which online (efficient) testing procedures can be derived! www.cs.jhu.edu/news/wanna-b...
📣 What should *ML explanations* convey, and how does one report these precisely and rigorously? @neuripsconf.bsky.social
come check
Jacopo Teneggi's work on Testing for Explanations via betting this afternoon! I *bet* you'll like it :) openreview.net/pdf?id=A0HSm... @hopkinsdsai.bsky.social
come check
Jacopo Teneggi's work on Testing for Explanations via betting this afternoon! I *bet* you'll like it :) openreview.net/pdf?id=A0HSm... @hopkinsdsai.bsky.social
December 11, 2024 at 6:12 PM
📣 What should *ML explanations* convey, and how does one report these precisely and rigorously? @neuripsconf.bsky.social
come check
Jacopo Teneggi's work on Testing for Explanations via betting this afternoon! I *bet* you'll like it :) openreview.net/pdf?id=A0HSm... @hopkinsdsai.bsky.social
come check
Jacopo Teneggi's work on Testing for Explanations via betting this afternoon! I *bet* you'll like it :) openreview.net/pdf?id=A0HSm... @hopkinsdsai.bsky.social
Reposted by Jeremias Sulam
NeurIPS paper: Excited for our work (with Iuliia Dmitrieva+Sergey Babkin) on
"realSEUDO for real-time calcium imaging analysis"
arxiv.org/abs/2405.15701
to be presented tomorrow (Thu 4:30-7:30PM). realSEUDO is a fully on-line method for cell detection and activity estimation that runs at >30Hz.
"realSEUDO for real-time calcium imaging analysis"
arxiv.org/abs/2405.15701
to be presented tomorrow (Thu 4:30-7:30PM). realSEUDO is a fully on-line method for cell detection and activity estimation that runs at >30Hz.
realSEUDO for real-time calcium imaging analysis
Closed-loop neuroscience experimentation, where recorded neural activity is used to modify the experiment on-the-fly, is critical for deducing causal connections and optimizing experimental time. A cr...
arxiv.org
December 11, 2024 at 2:23 PM
NeurIPS paper: Excited for our work (with Iuliia Dmitrieva+Sergey Babkin) on
"realSEUDO for real-time calcium imaging analysis"
arxiv.org/abs/2405.15701
to be presented tomorrow (Thu 4:30-7:30PM). realSEUDO is a fully on-line method for cell detection and activity estimation that runs at >30Hz.
"realSEUDO for real-time calcium imaging analysis"
arxiv.org/abs/2405.15701
to be presented tomorrow (Thu 4:30-7:30PM). realSEUDO is a fully on-line method for cell detection and activity estimation that runs at >30Hz.