Wojciech Masarczyk | DeepAI

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∙ 05/31/2023

The Tunnel Effect: Building Data Representations in Deep Neural Networks

Deep neural networks are widely known for their remarkable effectiveness...

0 Wojciech Masarczyk, et al. ∙

∙ 10/25/2022

Classification and Self-Supervised Regression of Arrhythmic ECG Signals Using Convolutional Neural Networks

Interpretation of electrocardiography (ECG) signals is required for diag...

0 Bartosz Grabowski, et al. ∙

∙ 07/30/2022

Reinforcement learning with experience replay and adaptation of action dispersion

Effective reinforcement learning requires a proper balance of exploratio...

0 Paweł Wawrzyński, et al. ∙

∙ 01/17/2022

Logarithmic Continual Learning

We introduce a neural network architecture that logarithmically reduces ...

0 Wojciech Masarczyk, et al. ∙

∙ 09/04/2021

On robustness of generative representations against catastrophic forgetting

Catastrophic forgetting of previously learned knowledge while learning n...

0 Wojciech Masarczyk, et al. ∙

∙ 06/23/2021

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

We propose a new method for unsupervised continual knowledge consolidati...

0 Kamil Deja, et al. ∙

∙ 03/30/2021

Reinforcement learning for optimization of variational quantum circuit architectures

The study of Variational Quantum Eigensolvers (VQEs) has been in the spo...

0 Mateusz Ostaszewski, et al. ∙

∙ 04/29/2020

Reducing catastrophic forgetting with learning on synthetic data

Catastrophic forgetting is a problem caused by neural networks' inabilit...

4 Wojciech Masarczyk, et al. ∙

∙ 09/12/2019

Effective transfer learning for hyperspectral image classification with deep convolutional neural networks

Hyperspectral imaging is a rich source of data, allowing for multitude o...

63 Wojciech Masarczyk, et al. ∙

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