54 citations · 60 across the 5 of their papers we have counts for
7 papers
Classification and Self-Supervised Regression of Arrhythmic ECG Signals Using Convolutional Neural Networks
Bartosz Grabowski, Przemysław Głomb, Wojciech Masarczyk +4
Interpretation of electrocardiography (ECG) signals is required for diagnosing cardiac arrhythmia. Recently, machine learning techniques have been applied for automated computer-ai…
Logarithmic Continual Learning
Wojciech Masarczyk, Paweł Wawrzyński, Daniel Marczak +2
We introduce a neural network architecture that logarithmically reduces the number of self-rehearsal steps in the generative rehearsal of continually learned models. In continual l…
On robustness of generative representations against catastrophic forgetting
Wojciech Masarczyk, Kamil Deja, Tomasz Trzciński
Catastrophic forgetting of previously learned knowledge while learning new tasks is a widely observed limitation of contemporary neural networks. Although many continual learning m…
Reinforcement learning for optimization of variational quantum circuit architectures
Mateusz Ostaszewski, Lea M. Trenkwalder, Wojciech Masarczyk +2
The study of Variational Quantum Eigensolvers (VQEs) has been in the spotlight in recent times as they may lead to real-world applications of near-term quantum devices. However, th…
BinPlay: A Binary Latent Autoencoder for Generative Replay Continual Learning
Kamil Deja, Paweł Wawrzyński, Daniel Marczak +2
We introduce a binary latent space autoencoder architecture to rehearse training samples for the continual learning of neural networks. The ability to extend the knowledge of a mod…
Reducing catastrophic forgetting with learning on synthetic data
Wojciech Masarczyk, Ivona Tautkute
Catastrophic forgetting is a problem caused by neural networks' inability to learn data in sequence. After learning two tasks in sequence, performance on the first one drops signif…