Eli Weinstein
@eliweinstein.bsky.social
Incoming assistant professor of chemistry at the Technical University of Denmark (DTU). Also at Jura Bio. machine learning, statistics, chemistry, biophysics
https://eweinstein.github.io/
https://eweinstein.github.io/
Paper: arxiv.org/abs/2510.16612
Blog: www.jura.bio/blog/leavs
Team: @lizbwood.bsky.social @highvariance.bsky.social @mgollub.bsky.social
Blog: www.jura.bio/blog/leavs
Team: @lizbwood.bsky.social @highvariance.bsky.social @mgollub.bsky.social
Accelerated Learning on Large Scale Screens using Generative Library Models
Biological machine learning is often bottlenecked by a lack of scaled data. One promising route to relieving data bottlenecks is through high throughput screens, which can experimentally test the acti...
arxiv.org
October 21, 2025 at 2:38 PM
We demonstrate empirically and prove theoretically that LeaVS can dramatically accelerate learning, increasing the effective dataset size by orders of magnitude.
October 21, 2025 at 2:38 PM
We demonstrate empirically and prove theoretically that LeaVS can dramatically accelerate learning, increasing the effective dataset size by orders of magnitude.
Crucially, it depends on jointly modifying the experimental protocol and the training algorithm: on their own, neither modification helps.
October 21, 2025 at 2:38 PM
Crucially, it depends on jointly modifying the experimental protocol and the training algorithm: on their own, neither modification helps.
This approach lets you focus limited measurements on the most informative datapoints, maximizing information gain without compromising reliability.
October 21, 2025 at 2:38 PM
This approach lets you focus limited measurements on the most informative datapoints, maximizing information gain without compromising reliability.
Second, modify the training algorithm: compensate for the missing negatives by incorporating the generative variational synthesis model into the objective.
October 21, 2025 at 2:38 PM
Second, modify the training algorithm: compensate for the missing negatives by incorporating the generative variational synthesis model into the objective.
First, modify the experiment: only measure positive examples of functional proteins. Don't spend a limited sequencing budget on any negatives.
October 21, 2025 at 2:38 PM
First, modify the experiment: only measure positive examples of functional proteins. Don't spend a limited sequencing budget on any negatives.
In this paper we describe a method to overcome this measurement bottleneck.
October 21, 2025 at 2:38 PM
In this paper we describe a method to overcome this measurement bottleneck.
To test, we can deliver billions of designs to different cells. But there is a cost to recovering those designs' function, to obtain (x,y) data.
October 21, 2025 at 2:38 PM
To test, we can deliver billions of designs to different cells. But there is a cost to recovering those designs' function, to obtain (x,y) data.
With variational synthesis, we can now build quadrillions of generative model-designed sequences. The bottleneck is now testing, not synthesis.
October 21, 2025 at 2:38 PM
With variational synthesis, we can now build quadrillions of generative model-designed sequences. The bottleneck is now testing, not synthesis.
Scaling up protein ML requires understanding and eliminating bottlenecks in the design-build-test-learn cycle.
October 21, 2025 at 2:38 PM
Scaling up protein ML requires understanding and eliminating bottlenecks in the design-build-test-learn cycle.
Reposted by Eli Weinstein
You can read more in our post at www.jurabio.com/blog/leavs; preprint forthcoming.
@jura.bsky.social @eliweinstein.bsky.social @mgollub.bsky.social @highvariance.bsky.social
@jura.bsky.social @eliweinstein.bsky.social @mgollub.bsky.social @highvariance.bsky.social
LeaVS: Accelerating learning for biological AI — JURA Bio, Inc.
A fundamental lesson of modern AI is that scale is essential: training bigger models on bigger datasets unlocks new capabilities. A fundamental lesson of AI engineering is that scaling up isn't trivia...
www.jurabio.com
September 22, 2025 at 12:15 PM
You can read more in our post at www.jurabio.com/blog/leavs; preprint forthcoming.
@jura.bsky.social @eliweinstein.bsky.social @mgollub.bsky.social @highvariance.bsky.social
@jura.bsky.social @eliweinstein.bsky.social @mgollub.bsky.social @highvariance.bsky.social
If you are interested in working with me as a student or postdoc, or otherwise collaborating, please reach out.
May 29, 2025 at 5:04 PM
If you are interested in working with me as a student or postdoc, or otherwise collaborating, please reach out.