Comparison of methods for phylogenetic B-cell lineage inference using time-resolved antibody repertoire simulations (AbSim). - Alexander Yermanos; Victor Greiff; Nike Julia Krautler; Ulrike Menzel; Andreas Dounas; Enkelejda Miho; Annette Oxenius; Tanja Stadler; Sai T. Reddy (Bioinform., 2017)

Modern Hopfield Networks and Attention for Immune Repertoire Classification. - Michael Widrich; Bernhard Schäfl; Milena Pavlovic; Hubert Ramsauer; Lukas Gruber; Markus Holzleitner; Johannes Brandstetter; Geir Kjetil Sandve; Victor Greiff; Sepp Hochreiter; Günter Klambauer (NeurIPS, 2020)

Benchmarking immunoinformatic tools for the analysis of antibody repertoire sequences. - Erand Smakaj; Lmar Babrak; Mats Ohlin; Mikhail Shugay; Bryan S. Briney; Deniz Tosoni; Christopher Galli; Vendi Grobelsek; Igor D'Angelo; Branden J. Olson; Sai T. Reddy; Victor Greiff; et al. (Bioinform., 2020)

immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking. - Cédric R. Weber; Rahmad Akbar; Alexander Yermanos; Milena Pavlovic; Igor Snapkov; Geir Kjetil Sandve; Sai T. Reddy; Victor Greiff (Bioinform., 2020)

Hopfield Networks is All You Need. - Hubert Ramsauer; Bernhard Schäfl; Johannes Lehner; Philipp Seidl; Michael Widrich; Lukas Gruber; Markus Holzleitner; Milena Pavlovic; Geir Kjetil Sandve; Victor Greiff; David P. Kreil; Michael Kopp 001; et al. (CoRR, 2020)

Modeling the Dynamics of T-Cell Development in the Thymus. - Philippe A. Robert; Heike Kunze-Schumacher; Victor Greiff; Andreas Krueger (Entropy, 2021)

The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires. - Milena Pavlovic; Lonneke Scheffer; Keshav Motwani; Chakravarthi Kanduri; Radmila Kompova; Nikolay Vazov; Knut Waagan; Fabian L. M. Bernal; Alexandre Almeida Costa; Brian Corrie; Rahmad Akbar; Ghadi S. Al Hajj; et al. (Nat. Mach. Intell., 2021)

TCRpower: quantifying the detection power of T-cell receptor sequencing with a novel computational pipeline calibrated by spike-in sequences. - Shiva Dahal-Koirala; Gabriel Balaban; Ralf Stefan Neumann; Lonneke Scheffer; Knut Erik Aslaksen Lundin; Victor Greiff; Ludvig Magne Sollid; Shuo-Wang Qiao; Geir Kjetil Sandve (Briefings Bioinform., 2022)

Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery. - Wiktoria Wilman; Sonia Wróbel; Weronika Bielska; Piotr Deszynski; Pawel Dudzic; Igor Jaszczyszyn; Jedrzej Kaniewski; Jakub Mlokosiewicz; Anahita Rouyan; Tadeusz Satlawa; Sandeep Kumar; Victor Greiff; et al. (Briefings Bioinform., 2022)

CompAIRR: ultra-fast comparison of adaptive immune receptor repertoires by exact and approximate sequence matching. - Torbjørn Rognes; Lonneke Scheffer; Victor Greiff; Geir Kjetil Sandve (Bioinform., 2022)

AntBO: Towards Real-World Automated Antibody Design with Combinatorial Bayesian Optimisation. - Mohammad Asif Khan 001; Alexander I. Cowen-Rivers; Derrick-Goh-Xin Deik; Antoine Grosnit; Kamil Dreczkowski; Philippe A. Robert; Victor Greiff; Rasul Tutunov; Dany Bou-Ammar; Jun Wang 012; Haitham Bou-Ammar (CoRR, 2022)

Improving generalization of machine learning-identified biomarkers with causal modeling: an investigation into immune receptor diagnostics. - Milena Pavlovic; Ghadi S. Al Hajj; Johan Pensar; Mollie Wood; Ludvig Magne Sollid; Victor Greiff; Geir Kjetil Sandve (CoRR, 2022)

Advancing protein language models with linguistics: a roadmap for improved interpretability. - Mai Ha Vu; Rahmad Akbar; Philippe A. Robert; Bartlomiej Swiatczak; Victor Greiff; Geir Kjetil Sandve; Dag Trygve Truslew Haug (CoRR, 2022)

ImmunoLingo: Linguistics-based formalization of the antibody language. - Mai Ha Vu; Philippe A. Robert; Rahmad Akbar; Bartlomiej Swiatczak; Geir Kjetil Sandve; Dag Trygve Truslew Haug; Victor Greiff (CoRR, 2022)

Unconstrained generation of synthetic antibody-antigen structures to guide machine learning methodology for antibody specificity prediction. - Philippe A. Robert; Rahmad Akbar; Robert Frank 006; Milena Pavlovic; Michael Widrich; Igor Snapkov; Andrei Slabodkin; Maria Chernigovskaya; Lonneke Scheffer; Eva Smorodina; Puneet Rawat; Brij Bhushan Mehta; et al. (Nat. Comput. Sci., 2022)

Access to ground truth at unconstrained size makes simulated data as indispensable as experimental data for bioinformatics methods development and benchmarking. - Geir Kjetil Sandve; Victor Greiff (Bioinform., 2022)

Best practices for machine learning in antibody discovery and development. - Leonard Wossnig; Norbert Furtmann; Andrew Buchanan; Sandeep Kumar; Victor Greiff (CoRR, 2023)

Bridging the neutralization gap for unseen antibodies. - Philippe A. Robert; Victor Greiff (Nat. Mac. Intell., 2023)

Linguistically inspired roadmap for building biologically reliable protein language models. - Mai Ha Vu; Rahmad Akbar; Philippe A. Robert; Bartlomiej Swiatczak; Geir Kjetil Sandve; Victor Greiff; Dag Trygve Truslew Haug (Nat. Mac. Intell., 2023)

Incorporating probabilistic domain knowledge into deep multiple instance learning. - 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 (ICML, 2024)

Predictability of antigen binding based on short motifs in the antibody CDRH3. - Lonneke Scheffer; Eric Emanuel Reber; Brij Bhushan Mehta; Milena Pavlovic; Maria Chernigovskaya; Eve Richardson; Rahmad Akbar; Fridtjof Lund-Johansen; Victor Greiff; Ingrid Hobæk Haff; Geir Kjetil Sandve (Briefings Bioinform., 2024)

Improving generalization of machine learning-identified biomarkers using causal modelling with examples from immune receptor diagnostics. - Milena Pavlovic; Ghadi S. Al Hajj; Chakravarthi Kanduri; Johan Pensar; Mollie Wood; Ludvig Magne Sollid; Victor Greiff; Geir Kjetil Sandve (Nat. Mac. Intell., 2024)

Linguistics-based formalization of the antibody language as a basis for antibody language models. - Mai Ha Vu; Philippe A. Robert; Rahmad Akbar; Bartlomiej Swiatczak; Geir Kjetil Sandve; Dag Trygve Truslew Haug; Victor Greiff (Nat. Comput. Sci., 2024)

Attribution assignment for deep-generative sequence models enables interpretability analysis using positive-only data. - Robert Frank 006; Michael Widrich; Rahmad Akbar; Günter Klambauer; Geir Kjetil Sandve; Philippe A. Robert; Victor Greiff (CoRR, 2025)