Kamil Deja

According to our database, Kamil Deja authored at least 26 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

There and Back Again: On the relation between noises, images, and their inversions in diffusion models.

Lukasz Staniszewski, Lukasz Kucinski, Kamil Deja

CoRR, 2024

Low-Rank Continual Personalization of Diffusion Models.

Lukasz Staniszewski, Katarzyna Zaleska, Kamil Deja

CoRR, 2024

Deep Generative Models for Proton Zero Degree Calorimeter Simulations in ALICE, CERN.

Patryk Bedkowski, Jan Dubinski, Kamil Deja, Przemyslaw Rokita

CoRR, 2024

Generative Diffusion Models for Fast Simulations of Particle Collisions at CERN.

Mikolaj Kita, Jan Dubinski, Przemyslaw Rokita, Kamil Deja

CoRR, 2024

Particle physics DL-simulation with control over generated data properties.

Karol Rogozinski, Jan Dubinski, Przemyslaw Rokita, Kamil Deja

CoRR, 2024

Particle identification with machine learning from incomplete data in the ALICE experiment.

Maja Karwowska, Lukasz Graczykowski, Kamil Deja, Milosz Kasak, Malgorzata Janik

CoRR, 2024

GUIDE: Guidance-based Incremental Learning with Diffusion Models.

Bartosz Cywinski, Kamil Deja, Tomasz Trzcinski, Bartlomiej Twardowski, Lukasz Kucinski

CoRR, 2024

Machine-learning-based particle identification with missing data.

Milosz Kasak, Kamil Deja, Maja Karwowska, Monika Jakubowska, Lukasz Graczykowski, Malgorzata Janik

CoRR, 2024

Looking Through the Past: Better Knowledge Retention for Generative Replay in Continual Learning.

Valeriya Khan, Sebastian Cygert, Kamil Deja, Tomasz Trzcinski, Bartlomiej Twardowski

IEEE Access, 2024

2023

Adapt & Align: Continual Learning with Generative Models Latent Space Alignment.

Kamil Deja, Bartosz Cywinski, Jan Rybarczyk, Tomasz Trzcinski

CoRR, 2023

Bayesian Flow Networks in Continual Learning.

Mateusz Pyla, Kamil Deja, Bartlomiej Twardowski, Tomasz Trzcinski

CoRR, 2023

Machine Learning methods for simulating particle response in the Zero Degree Calorimeter at the ALICE experiment, CERN.

Jan Dubinski, Kamil Deja, Sandro Wenzel, Przemyslaw Rokita, Tomasz Trzcinski

CoRR, 2023

Exploring Continual Learning of Diffusion Models.

Michal Zajac, Kamil Deja, Anna Kuzina, Jakub M. Tomczak, Tomasz Trzcinski, Florian Shkurti, Piotr Milos

CoRR, 2023

Learning Data Representations with Joint Diffusion Models.

Kamil Deja, Tomasz Trzcinski, Jakub M. Tomczak

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Diffusion-based accent modelling in speech synthesis.

Kamil Deja, Georgi Tinchev, Marta Czarnowska, Marius Cotescu, Jasha Droppo

Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

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

Georgi Tinchev, Marta Czarnowska, Kamil Deja, Kayoko Yanagisawa, Marius Cotescu

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Logarithmic Continual Learning.

Wojciech Masarczyk, Pawel Wawrzynski, Daniel Marczak, Kamil Deja, Tomasz Trzcinski

IEEE Access, 2022

On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models.

Kamil Deja, Anna Kuzina, Tomasz Trzcinski, Jakub M. Tomczak

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Automatic Evaluation of Speaker Similarity.

Kamil Deja, Ariadna Sánchez, Julian Roth, Marius Cotescu

Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

Multiband VAE: Latent Space Alignment for Knowledge Consolidation in Continual Learning.

Kamil Deja, Pawel Wawrzynski, Wojciech Masarczyk, Daniel Marczak, Tomasz Trzcinski

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Selectively Increasing the Diversity of GAN-Generated Samples.

Jan Dubinski, Kamil Deja, Sandro Wenzel, Przemyslaw Rokita, Tomasz Trzcinski

Proceedings of the Neural Information Processing - 29th International Conference, 2022

2021

Multiband VAE: Latent Space Partitioning for Knowledge Consolidation in Continual Learning.

Kamil Deja, Pawel Wawrzynski, Daniel Marczak, Wojciech Masarczyk, Tomasz Trzcinski

CoRR, 2021

End-to-End Sinkhorn Autoencoder With Noise Generator.

Kamil Deja, Jan Dubinski, Piotr Nowak, Sandro Wenzel, Przemyslaw Spurek, Tomasz Trzcinski

IEEE Access, 2021

BinPlay: A Binary Latent Autoencoder for Generative Replay Continual Learning.

Kamil Deja, Pawel Wawrzynski, Daniel Marczak, Wojciech Masarczyk, Tomasz Trzcinski

Proceedings of the International Joint Conference on Neural Networks, 2021

On Robustness of Generative Representations Against Catastrophic Forgetting.

Wojciech Masarczyk, Kamil Deja, Tomasz Trzcinski

Proceedings of the Neural Information Processing - 28th International Conference, 2021

2020

End-to-end Sinkhorn Autoencoder with Noise Generator.

Kamil Deja, Jan Dubinski, Piotr Nowak, Sandro Wenzel, Tomasz Trzcinski

CoRR, 2020