Kamil Deja

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 33

Top Topics

Data Representations

Diffusion Models

Top Venues

Publications

Valeriya Khan, Sebastian Cygert, Kamil Deja, Tomasz Trzcinski, Bartlomiej Twardowski
Looking Through the Past: Better Knowledge Retention for Generative Replay in Continual Learning. IEEE Access 12 (2024)
Milosz Kasak, Kamil Deja, Maja Karwowska, Monika Jakubowska, Lukasz Graczykowski, Malgorzata Janik
Machine-learning-based particle identification with missing data. CoRR (2024)
Patryk Bedkowski, Jan Dubinski, Kamil Deja, Przemyslaw Rokita
Deep Generative Models for Proton Zero Degree Calorimeter Simulations in ALICE, CERN. CoRR (2024)
Karol Rogozinski, Jan Dubinski, Przemyslaw Rokita, Kamil Deja
Particle physics DL-simulation with control over generated data properties. CoRR (2024)
Bartosz Cywinski, Kamil Deja, Tomasz Trzcinski, Bartlomiej Twardowski, Lukasz Kucinski
GUIDE: Guidance-based Incremental Learning with Diffusion Models. CoRR (2024)
Mikolaj Kita, Jan Dubinski, Przemyslaw Rokita, Kamil Deja
Generative Diffusion Models for Fast Simulations of Particle Collisions at CERN. CoRR (2024)
Maja Karwowska, Lukasz Graczykowski, Kamil Deja, Milosz Kasak, Malgorzata Janik
Particle identification with machine learning from incomplete data in the ALICE experiment. CoRR (2024)
Georgi Tinchev, Marta Czarnowska, Kamil Deja, Kayoko Yanagisawa, Marius Cotescu
Modelling Low-Resource Accents Without Accent-Specific TTS Frontend. ICASSP (2023)
Mateusz Pyla, Kamil Deja, Bartlomiej Twardowski, Tomasz Trzcinski
Bayesian Flow Networks in Continual Learning. CoRR (2023)
Valeriya Khan, Sebastian Cygert, Kamil Deja, Tomasz Trzcinski, Bartlomiej Twardowski
Looking through the past: better knowledge retention for generative replay in continual learning. CoRR (2023)
Kamil Deja, Tomasz Trzcinski, Jakub M. Tomczak
Learning Data Representations with Joint Diffusion Models. CoRR (2023)
Michal Zajac, Kamil Deja, Anna Kuzina, Jakub M. Tomczak, Tomasz Trzcinski, Florian Shkurti, Piotr Milos
Exploring Continual Learning of Diffusion Models. CoRR (2023)
Kamil Deja, Georgi Tinchev, Marta Czarnowska, Marius Cotescu, Jasha Droppo
Diffusion-based accent modelling in speech synthesis. INTERSPEECH (2023)
Jan Dubinski, Kamil Deja, Sandro Wenzel, Przemyslaw Rokita, Tomasz Trzcinski
Machine Learning methods for simulating particle response in the Zero Degree Calorimeter at the ALICE experiment, CERN. CoRR (2023)
Kamil Deja, Bartosz Cywinski, Jan Rybarczyk, Tomasz Trzcinski
Adapt & Align: Continual Learning with Generative Models Latent Space Alignment. CoRR (2023)
Kamil Deja, Tomasz Trzcinski, Jakub M. Tomczak
Learning Data Representations with Joint Diffusion Models. ECML/PKDD (2) (2023)
Georgi Tinchev, Marta Czarnowska, Kamil Deja, Kayoko Yanagisawa, Marius Cotescu
Modelling low-resource accents without accent-specific TTS frontend. CoRR (2023)
Kamil Deja, Pawel Wawrzynski, Wojciech Masarczyk, Daniel Marczak, Tomasz Trzcinski
Multiband VAE: Latent Space Alignment for Knowledge Consolidation in Continual Learning. IJCAI (2022)
Jan Dubinski, Kamil Deja, Sandro Wenzel, Przemyslaw Rokita, Tomasz Trzcinski
Selectively increasing the diversity of GAN-generated samples. CoRR (2022)
Jan Dubinski, Kamil Deja, Sandro Wenzel, Przemyslaw Rokita, Tomasz Trzcinski
Selectively Increasing the Diversity of GAN-Generated Samples. ICONIP (1) (2022)
Kamil Deja, Anna Kuzina, Tomasz Trzcinski, Jakub M. Tomczak
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models. NeurIPS (2022)
Kamil Deja, Ariadna Sanchez, Julian Roth, Marius Cotescu
Automatic Evaluation of Speaker Similarity. INTERSPEECH (2022)
Kamil Deja, Ariadna Sanchez, Julian Roth, Marius Cotescu
Automatic Evaluation of Speaker Similarity. CoRR (2022)
Wojciech Masarczyk, Pawel Wawrzynski, Daniel Marczak, Kamil Deja, Tomasz Trzcinski
Logarithmic Continual Learning. CoRR (2022)
Kamil Deja, Anna Kuzina, Tomasz Trzcinski, Jakub M. Tomczak
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models. CoRR (2022)
Wojciech Masarczyk, Pawel Wawrzynski, Daniel Marczak, Kamil Deja, Tomasz Trzcinski
Logarithmic Continual Learning. IEEE Access 10 (2022)
Kamil Deja, Jan Dubinski, Piotr Nowak, Sandro Wenzel, Przemyslaw Spurek, Tomasz Trzcinski
End-to-End Sinkhorn Autoencoder With Noise Generator. IEEE Access 9 (2021)
Kamil Deja, Pawel Wawrzynski, Daniel Marczak, Wojciech Masarczyk, Tomasz Trzcinski
Multiband VAE: Latent Space Partitioning for Knowledge Consolidation in Continual Learning. CoRR (2021)
Wojciech Masarczyk, Kamil Deja, Tomasz Trzcinski
On robustness of generative representations against catastrophic forgetting. CoRR (2021)
Wojciech Masarczyk, Kamil Deja, Tomasz Trzcinski
On Robustness of Generative Representations Against Catastrophic Forgetting. ICONIP (6) (2021)
Kamil Deja, Pawel Wawrzynski, Daniel Marczak, Wojciech Masarczyk, Tomasz Trzcinski
BinPlay: A Binary Latent Autoencoder for Generative Replay Continual Learning. IJCNN (2021)
Kamil Deja, Jan Dubinski, Piotr Nowak, Sandro Wenzel, Tomasz Trzcinski
End-to-end Sinkhorn Autoencoder with Noise Generator. CoRR (2020)
Kamil Deja, Pawel Wawrzynski, Daniel Marczak, Wojciech Masarczyk, Tomasz Trzcinski
BinPlay: A Binary Latent Autoencoder for Generative Replay Continual Learning. CoRR (2020)