Aaditya 'Adi' Prakash
@aaditya_prakash
Foundation Models for drug discovery. Staff Machine Learning Scientist at Spring Science (ex: PathAI, Philips Research, Microsoft Research). PhD ML.
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We are releasing a benchmarking dataset that will enable better representation learning for high-content imaging. We also show the impact of various normalization on embeddings.
We are releasing the Spring Inflammasome Benchmark Dataset, along with our poster at #SLAS2023! github.com/spring-discove… Details in thread
I am always amazed with the inference speed of @GroqInc . Given Kimi K2 is a super big model, the results come almost instantaneously. 👏
As many of you know, over the past few months I have been sharing Prompt Engineering resources in different forms. I have now compiled them all into a cohesive publication and uploaded to arxiv: arxiv.org/abs/2401.14423
This is just wild! Nov 9: @wtgowers, Green, Manners, and Tao prove the polynomial Freiman-Ruzsa conjecture in char 2. arxiv.org/abs/2311.05762 Nov 18: Tao announces that he wants to formalize it in Lean, building on Mathlib. terrytao.wordpress.com/2023/11/18/for… Dec 4: One little theorem…
Come get live, 1:1 demos of AI software that gives scientists superpowers @ #SLAS2023, and also check out our posters: springdiscovery.com/slas Learn all about using AI to go beyond traditional image analysis, check out our new public benchmark dataset, and more...
Looking forward to this webinar. Ruff an extremely fast linting for Python (when I say extreme, I mean it) github.com/charliermarsh/… info.jetbrains.com/pycharm-webina… @charliermarsh 👏
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Ruff: Faster Python Linting With Rust
If you want to explore an amazing Cell Painting dataset - JUMP-CP : 3M images, 75M single-cells, 5 channels, 306 compounds, and 6 genetic perturbations (ORF & CRISPR). Any feedback is welcome.
Yep! Cell Painting fits the bill. You can grab images from here springdiscovery.com/jump-cp though generally if people are looking for random markers cellimagelibrary.org
Stop using the elbow criterion for k-means and how to choose the number of clusters instead. (arXiv:2212.12189v1 [stat.ML]) ift.tt/TJaIE2X
#SABCS22 | Poster | Prognostic & Predictive Factors Quantitative analysis of fiber-level collagen features in H&E whole-slide images predicts neoadjuvant therapy response in patients with HER2+ #breastcancer @EMittendorfMD @aaditya_prakash @BusemBKurt @SchnittStuart @stolaney1
Visual introduction to optimal transport. My first Manim video (best seen in full screen)! Special thanks to @gabrielpeyre for his suggestions.
This might be the best explanation of the Fourier Transform on the internet: jezzamon.com/fourier/index.… author: @jezzamonn
Our awesome Lead Scientist - Rachel Jacobson, explains how we use machine learning to harness the complexities of inflammasome biology for novel drug discovery youtube.com/watch?v=7LN4mT…
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Using machine learning to harness the complexities of inflammasome...
The inventor of Confocal Microscopy is none other than Marvin Minsky, inventor of Artificial Intelligence web.media.mit.edu/~minsky/papers…
Today I learned that there is a board that certified medical illustrators. You can find some of the awesome illustrations (including the famous Coronavirus image) here: ami.org/medical-illust…
Interpretability of Machine Learning in Medicine is very important. However, Multiple Instance Learning (used with large images like Pathology) is not interpretable. We propose Additive MIL (similar to SHAP), which solves this problem: arxiv.org/abs/2206.01794 Feedbacks welcome.
Yep! Cell Painting fits the bill. You can grab images from here springdiscovery.com/jump-cp though generally if people are looking for random markers cellimagelibrary.org
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