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Deja, Kamil
142  Ergebnisse:
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1

Particle identification with machine learning in ALICE Run :

Karwowska, Maja ; Jakubowska, Monika ; Graczykowski, Łukasz...
EPJ Web of Conferences.  295 (2024)  - p. 09029 , 2024
Link: https://doi.org/10.1051/..
 
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2

Looking Through the Past: Better Knowledge Retention for Ge..:

Khan, Valeriya ; Cygert, Sebastian ; Deja, Kamil..
IEEE Access.  12 (2024)  - p. 45309-45317 , 2024
Link: https://doi.org/10.1109/..
 
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3

Selectively Increasing the Diversity of GAN-Generated Sampl..:

, In: Neural Information Processing; Lecture Notes in Computer Science,
Dubiński, Jan ; Deja, Kamil ; Wenzel, Sandro.. - p. 260-270 , 2023
Link: https://doi.org/10.1007/..
 
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4

Modelling Low-Resource Accents Without Accent-Specific TTS ..:

, In: ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
Tinchev, Georgi ; Czarnowska, Marta ; Deja, Kamil.. - p. 1-5 , 2023
Link: https://doi.org/10.1109/..
 
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5

Learning Data Representations with Joint Diffusion Models:

, In: Machine Learning and Knowledge Discovery in Databases: Research Track; Lecture Notes in Computer Science,
Deja, Kamil ; Trzciński, Tomasz ; Tomczak, Jakub M. - p. 543-559 , 2023
Link: https://doi.org/10.1007/..
 
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6

Logarithmic Continual Learning:

Masarczyk, Wojciech ; Wawrzynski, Pawel ; Marczak, Daniel..
IEEE Access.  10 (2022)  - p. 117001-117010 , 2022
Link: https://doi.org/10.1109/..
 
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7

End-to-End Sinkhorn Autoencoder With Noise Generator:

Deja, Kamil ; Dubinski, Jan ; Nowak, Piotr...
IEEE Access.  9 (2021)  - p. 7211-7219 , 2021
Link: https://doi.org/10.1109/..
 
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8

On Robustness of Generative Representations Against Catastr..:

, In: Communications in Computer and Information Science; Neural Information Processing,
Masarczyk, Wojciech ; Deja, Kamil ; Trzcinski, Tomasz - p. 325-333 , 2021
Link: https://doi.org/10.1007/..
 
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9

Generative Models for Fast Cluster Simulations in the TPC f..:

, In: Advances in Intelligent Systems and Computing; Information Technology, Systems Research, and Computational Physics,
for the ALICE Collaboration ; Deja, Kamil ; Trzciński, Tomasz. - p. 267-280 , 2019
Link: https://doi.org/10.1007/..
 
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10

Generative models for fast cluster simulations in the TPC f..:

Deja, Kamil ; Trzcin´ski, Tomasz ; Graczykowski, Łukasz...
EPJ Web of Conferences.  214 (2019)  - p. 06003 , 2019
Link: https://doi.org/10.1051/..
 
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11

Using machine learning for particle identification in ALICE:

Graczykowski, Łukasz Kamil ; Jakubowska, Monika ; Deja, Kamil Rafał.
Journal of Instrumentation.  17 (2022)  7 - p. C07016 , 2022
Link: https://doi.org/10.1088/..
 
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12

Exploring Continual Learning of Diffusion Models:

Zając, Michał ; Deja, Kamil ; Kuzina, Anna...
http://arxiv.org/abs/2303.15342.  , 2023
Link: http://arxiv.org/abs/230..
 
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13

Learning Data Representations with Joint Diffusion Models:

Deja, Kamil ; Trzcinski, Tomasz ; Tomczak, Jakub M
http://arxiv.org/abs/2301.13622.  , 2023
Link: http://arxiv.org/abs/230..
 
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14

Bayesian Flow Networks in Continual Learning:

Pyla, Mateusz ; Deja, Kamil ; Twardowski, Bartłomiej.
http://arxiv.org/abs/2310.12001.  , 2023
Link: http://arxiv.org/abs/231..
 
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15

Machine-learning-based particle identification with missing..:

Kasak, Miłosz ; Deja, Kamil ; Karwowska, Maja...
http://arxiv.org/abs/2401.01905.  , 2023
Link: http://arxiv.org/abs/240..
 
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