Unveiling the strong interaction among hadrons at the LHC
Nature 588 (7837), 232-238, 2020
157 2020 Generative models for fast cluster simulations in the TPC for the ALICE experiment K Deja, T Trzcinski, L Graczykowski
Proceedings, 23rd International Conference on Computing in High Energy and …, 2019
35 2019 On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models K Deja, A Kuzina, T Trzciński, JM Tomczak
NeurIPS 2022, 2022
19 2022 End-to-end sinkhorn autoencoder with noise generator K Deja, J Dubiński, P Nowak, S Wenzel, P Spurek, T Trzcinski
IEEE Access 9, 7211-7219, 2020
14 2020 Using machine learning for particle identification in ALICE ŁK Graczykowski, M Jakubowska, KR Deja, M Kabus, Alice Collaboration
Journal of Instrumentation 17 (07), C07016, 2022
9 2022 Binplay: A binary latent autoencoder for generative replay continual learning K Deja, P Wawrzyński, D Marczak, W Masarczyk, T Trzciński
2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
9 2021 SISSA: Using Machine Learning techniques for Data Quality Monitoring in CMS and ALICE experiments KR Deja
PoS, 236, 2019
7 2019 ALICE et al. 2020 S Acharya
Phys. Lett. B 804, 135375, 2020
6 * 2020 Assigning quality labels in the high-energy physics experiment ALICE using machine learning algorithms T Trzcinski, K Deja
Acta Phys. Polon. Suppl. A 11 (647), 10.5506, 2018
5 2018 Learning data representations with joint diffusion models K Deja, T Trzciński, JM Tomczak
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023
4 2023 Logarithmic continual learning W Masarczyk, P Wawrzyński, D Marczak, K Deja, T Trzciński
IEEE Access 10, 117001-117010, 2022
4 2022 Automatic evaluation of speaker similarity K Deja, A Sanchez, J Roth, M Cotescu
Interspeech 2022, 2022
4 2022 Multiband VAE: latent space alignment for knowledge consolidation in continual learning K Deja, P Wawrzynski, W Masarczyk, D Marczak, T Trzciński
IJCAI 2022, 2022
4 2022 On robustness of generative representations against catastrophic forgetting W Masarczyk, K Deja, T Trzcinski
International Conference on Neural Information Processing, 325-333, 2021
4 2021 Exploring continual learning of diffusion models M Zając, K Deja, A Kuzina, JM Tomczak, T Trzciński, F Shkurti, P Miłoś
arXiv preprint arXiv:2303.15342, 2023
3 2023 Machine Learning methods for simulating particle response in the Zero Degree Calorimeter at the ALICE experiment, CERN J Dubiński, K Deja, S Wenzel, P Rokita, T Trzciński
AIP Conference Proceedings 3061 (1), 2024
2 2024 Looking through the past: better knowledge retention for generative replay in continual learning V Khan, S Cygert, B Twardowski, T Trzciński
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
2 2023 Selectively increasing the diversity of GAN-generated samples J Dubiński, K Deja, S Wenzel, P Rokita, T Trzcinski
International Conference on Neural Information Processing, 260-270, 2022
2 2022 Multiband VAE: Latent Space Partitioning for Knowledge Consolidation in Continual Learning. K Deja, P Wawrzynski, D Marczak, W Masarczyk, T Trzcinski
arXiv preprint arXiv:2106.12196, 2021
2 2021 Measurement of prompt S Acharya, D Dąbrowski, K Deja, Ł Graczykowski, M Jakubowska, ...
Journal of High Energy Physics 2019 (12), 2019
1 2019 
Tomasz TrzcinskiWarsaw University of Technology, Tooploox, IDEAS NCBRПодтвержден адрес электронной почты в домене pw.edu.pl
