Taylor Joren
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    • Concept bottleneck language models for protein design
    • Guided Generation of B-cell Receptors with Conditional Walk-Jump Sampling
    • Lab-in-the-loop therapeutic antibody design with deep learning
    • Learning the language of antibody hypervariability
    • Prediction of single-cell RNA expression profiles in live cells by Raman microscopy with Raman2RNA
    • Cramming protein language model training in 24 GPU hours
    • Surface ID: a geometry-aware system for protein molecular surface comparison
    • Interpreting Raman spectra using machine learning: towards a non-invasive method of characterizing single cells
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Concept bottleneck language models for protein design

Apr 1, 2025·
Aya Abdelsalam Ismail
,
Tuomas Oikarinen
,
Amy Wang
,
Julius Adebayo
,
Samuel Stanton
,
Héctor Corrada Bravo
Taylor Joren
Taylor Joren
,
Et Al.
· 0 min read
Source Document
Type
Conference paper
Publication
International Conference on Learning Representations (ICLR)
Last updated on Jul 16, 2026
Taylor Joren
Authors
Taylor Joren
Senior Machine Learning Scientist
Guided Generation of B-cell Receptors with Conditional Walk-Jump Sampling Apr 1, 2025 →

© 2026 Taylor Joren. This work is licensed under CC BY NC ND 4.0

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