Grzegorzek, Tomasz

Discovering highly potent antimicrobial peptides with deep generative model HydrAMP

Szymczak, P., Możejko, M., Grzegorzek, T., Jurczak, R., Bauer, M., Neubauer, D., Sikora, K., Michalski, M., Sroka, J., Setny, P., et al. (2022) · Nature Communications

Antimicrobial Peptides and ActivitiesComputational Drug Discovery Methods

Cited by 231

Discovering highly potent antimicrobial peptides with deep generative model HydrAMP

Szymczak, P., Możejko, M., Grzegorzek, T., Jurczak, R., Bauer, M., Neubauer, D., Sikora, K., Michalski, M., Sroka, J., Setny, P., et al. (2023) · Nature Communications

Antimicrobial Peptides and ActivitiesComputational Drug Discovery Methods

Cited by 231

Nemotron-4 340B Technical Report

Nvidia, :, Adler, B., Agarwal, N., Aithal, A., Anh, D. H., Bhattacharya, P., Brundyn, A., Casper, J., Catanzaro, B., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 66

Llama-Nemotron: Efficient Reasoning Models

Bercovich, A., Levy, I., Golan, I., Dabbah, M., El-Yaniv, R., Puny, O., Galil, I., Moshe, Z., Ronen, T., Nabwani, N., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1