Victor Greiff

Orcid: 0000-0003-2622-5032

According to our database1, Victor Greiff authored at least 23 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Linguistics-based formalization of the antibody language as a basis for antibody language models.
Nat. Comput. Sci., June, 2024

Improving generalization of machine learning-identified biomarkers using causal modelling with examples from immune receptor diagnostics.
Nat. Mac. Intell., 2024

Predictability of antigen binding based on short motifs in the antibody CDRH3.
Briefings Bioinform., 2024

Incorporating probabilistic domain knowledge into deep multiple instance learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Linguistically inspired roadmap for building biologically reliable protein language models.
Nat. Mac. Intell., May, 2023

Bridging the neutralization gap for unseen antibodies.
Nat. Mac. Intell., January, 2023

Best practices for machine learning in antibody discovery and development.
CoRR, 2023

2022
Access to ground truth at unconstrained size makes simulated data as indispensable as experimental data for bioinformatics methods development and benchmarking.
Bioinform., October, 2022

Unconstrained generation of synthetic antibody-antigen structures to guide machine learning methodology for antibody specificity prediction.
Nat. Comput. Sci., 2022

ImmunoLingo: Linguistics-based formalization of the antibody language.
CoRR, 2022

Advancing protein language models with linguistics: a roadmap for improved interpretability.
CoRR, 2022

Improving generalization of machine learning-identified biomarkers with causal modeling: an investigation into immune receptor diagnostics.
CoRR, 2022

AntBO: Towards Real-World Automated Antibody Design with Combinatorial Bayesian Optimisation.
CoRR, 2022

CompAIRR: ultra-fast comparison of adaptive immune receptor repertoires by exact and approximate sequence matching.
Bioinform., 2022

Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery.
Briefings Bioinform., 2022

TCRpower: quantifying the detection power of T-cell receptor sequencing with a novel computational pipeline calibrated by spike-in sequences.
Briefings Bioinform., 2022

2021
The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires.
Nat. Mach. Intell., 2021

Modeling the Dynamics of T-Cell Development in the Thymus.
Entropy, 2021

2020
Hopfield Networks is All You Need.
CoRR, 2020

immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking.
Bioinform., 2020

Benchmarking immunoinformatic tools for the analysis of antibody repertoire sequences.
Bioinform., 2020

Modern Hopfield Networks and Attention for Immune Repertoire Classification.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2017
Comparison of methods for phylogenetic B-cell lineage inference using time-resolved antibody repertoire simulations (AbSim).
Bioinform., 2017


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