71 citations · 147 across the 7 of their papers we have counts for
8 papers
Attribution assignment for deep-generative sequence models enables interpretability analysis using positive-only data
Robert Frank, Michael Widrich, Rahmad Akbar +4
Generative machine learning models offer a powerful framework for therapeutic design by efficiently exploring large spaces of biological sequences enriched for desirable properties…
ImmunoLingo: Linguistics-based formalization of the antibody language
Mai Ha Vu, Philippe A. Robert, Rahmad Akbar +4
Apparent parallels between natural language and biological sequence have led to a recent surge in the application of deep language models (LMs) to the analysis of antibody and othe…
Linguistically inspired roadmap for building biologically reliable protein language models
Mai Ha Vu, Rahmad Akbar, Philippe A. Robert +4
Deep neural-network-based language models (LMs) are increasingly applied to large-scale protein sequence data to predict protein function. However, being largely black-box models a…
Improving generalization of machine learning-identified biomarkers with causal modeling: an investigation into immune receptor diagnostics
Milena Pavlović, Ghadi S. Al Hajj, Chakravarthi Kanduri +5
Machine learning is increasingly used to discover diagnostic and prognostic biomarkers from high-dimensional molecular data. However, a variety of factors related to experimental d…
AntBO: Towards Real-World Automated Antibody Design with Combinatorial Bayesian Optimisation
Asif Khan, Alexander I. Cowen-Rivers, Antoine Grosnit +12
Antibodies are canonically Y-shaped multimeric proteins capable of highly specific molecular recognition. The CDRH3 region located at the tip of variable chains of an antibody domi…
A physical protocol for observers near the boundary to obtain bulk information in quantum gravity
Chandramouli Chowdhury, Olga Papadoulaki, Suvrat Raju
We consider a set of observers who live near the boundary of global AdS, and are allowed to act only with simple low-energy unitaries and make measurements in a small interval of t…
Modern Hopfield Networks and Attention for Immune Repertoire Classification
Michael Widrich, Bernhard Schäfl, Hubert Ramsauer +8
A central mechanism in machine learning is to identify, store, and recognize patterns. How to learn, access, and retrieve such patterns is crucial in Hopfield networks and the more…
Augmenting adaptive immunity: progress and challenges in the quantitative engineering and analysis of adaptive immune receptor repertoires
Alex J. Brown, Igor Snapkov, Rahmad Akbar +4
The adaptive immune system is a natural diagnostic and therapeutic. It recognizes threats earlier than clinical symptoms manifest and neutralizes antigen with exquisite specificity…