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Victor Greiff
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2020 – today
- 2024
- [j14]Milena Pavlovic
, Ghadi S. Al Hajj
Improving generalization of machine learning-identified biomarkers using causal modelling with examples from immune receptor diagnostics. Nat. Mac. Intell. 6(1): 15-24 (2024) - [j13]Mai Ha Vu
Linguistics-based formalization of the antibody language as a basis for antibody language models. Nat. Comput. Sci. 4(6): 412-422 (2024) - [c2]Ghadi S. Al Hajj, Aliaksandr Hubin, Chakravarthi Kanduri, Milena Pavlovic, Knut Dagestad Rand, Michael Widrich, Anne H. Schistad Solberg, Victor Greiff, Johan Pensar, Günter Klambauer, Geir Kjetil Sandve:
Incorporating probabilistic domain knowledge into deep multiple instance learning. ICML 2024 - 2023
- [j12]Philippe A. Robert
Bridging the neutralization gap for unseen antibodies. Nat. Mac. Intell. 5(1): 8-10 (2023) - [j11]Mai Ha Vu
Linguistically inspired roadmap for building biologically reliable protein language models. Nat. Mac. Intell. 5(5): 485-496 (2023) - [i7]Leonard Wossnig, Norbert Furtmann, Andrew Buchanan, Sandeep Kumar, Victor Greiff:
Best practices for machine learning in antibody discovery and development. CoRR abs/2312.08470 (2023) - 2022
- [j10]Shiva Dahal-Koirala
TCRpower: quantifying the detection power of T-cell receptor sequencing with a novel computational pipeline calibrated by spike-in sequences. Briefings Bioinform. 23(2) (2022) - [j9]Wiktoria Wilman, Sonia Wróbel, Weronika Bielska, Piotr Deszynski, Pawel Dudzic, Igor Jaszczyszyn, Jedrzej Kaniewski, Jakub Mlokosiewicz, Anahita Rouyan, Tadeusz Satlawa, Sandeep Kumar
Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery. Briefings Bioinform. 23(4) (2022) - [j8]Torbjørn Rognes
CompAIRR: ultra-fast comparison of adaptive immune receptor repertoires by exact and approximate sequence matching. Bioinform. 38(17): 4230-4232 (2022) - [j7]Geir Kjetil Sandve
Access to ground truth at unconstrained size makes simulated data as indispensable as experimental data for bioinformatics methods development and benchmarking. Bioinform. 38(21): 4994-4996 (2022) - [j6]Philippe A. Robert
Unconstrained generation of synthetic antibody-antigen structures to guide machine learning methodology for antibody specificity prediction. Nat. Comput. Sci. 2(12): 845-865 (2022) - [i6]Mohammad Asif Khan, Alexander I. Cowen-Rivers, Derrick-Goh-Xin Deik, Antoine Grosnit, Kamil Dreczkowski, Philippe A. Robert, Victor Greiff, Rasul Tutunov, Dany Bou-Ammar, Jun Wang, Haitham Bou-Ammar:
AntBO: Towards Real-World Automated Antibody Design with Combinatorial Bayesian Optimisation. CoRR abs/2201.12570 (2022) - [i5]Milena Pavlovic, Ghadi S. Al Hajj, Johan Pensar, Mollie Wood, Ludvig Magne Sollid, Victor Greiff, Geir Kjetil Sandve:
Improving generalization of machine learning-identified biomarkers with causal modeling: an investigation into immune receptor diagnostics. CoRR abs/2204.09291 (2022) - [i4]Mai Ha Vu, Rahmad Akbar, Philippe A. Robert, Bartlomiej Swiatczak, Victor Greiff, Geir Kjetil Sandve, Dag Trygve Truslew Haug:
Advancing protein language models with linguistics: a roadmap for improved interpretability. CoRR abs/2207.00982 (2022) - [i3]Mai Ha Vu, Philippe A. Robert, Rahmad Akbar, Bartlomiej Swiatczak, Geir Kjetil Sandve, Dag Trygve Truslew Haug, Victor Greiff:
ImmunoLingo: Linguistics-based formalization of the antibody language. CoRR abs/2209.12635 (2022) - 2021
- [j5]Philippe A. Robert
Modeling the Dynamics of T-Cell Development in the Thymus. Entropy 23(4): 437 (2021) - [j4]Milena Pavlovic
The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires. Nat. Mach. Intell. 3(11): 936-944 (2021) - 2020
- [j3]Erand Smakaj, Lmar Babrak
Benchmarking immunoinformatic tools for the analysis of antibody repertoire sequences. Bioinform. 36(6): 1731-1739 (2020) - [j2]Cédric R. Weber
immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking. Bioinform. 36(11): 3594-3596 (2020) - [c1]Michael Widrich, Bernhard Schäfl, Milena Pavlovic, Hubert Ramsauer, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter, Geir Kjetil Sandve, Victor Greiff, Sepp Hochreiter, Günter Klambauer:
Modern Hopfield Networks and Attention for Immune Repertoire Classification. NeurIPS 2020 - [i2]Michael Widrich
Modern Hopfield Networks and Attention for Immune Repertoire Classification. CoRR abs/2007.13505 (2020) - [i1]Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner, Philipp Seidl, Michael Widrich
Hopfield Networks is All You Need. CoRR abs/2008.02217 (2020)
2010 – 2019
- 2017
- [j1]Alexander Yermanos, Victor Greiff
Comparison of methods for phylogenetic B-cell lineage inference using time-resolved antibody repertoire simulations (AbSim). Bioinform. 33(24): 3938-3946 (2017)
Coauthor Index
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