393 citations · 835 across the 28 of their papers we have counts for
3 papers · 1 filter
On consequences of finetuning on data with highly discriminative features
Wojciech Masarczyk, Tomasz Trzciński, Mateusz Ostaszewski
In the era of transfer learning, training neural networks from scratch is becoming obsolete. Transfer learning leverages prior knowledge for new tasks, conserving computational res…
Enhancing variational quantum state diagonalization using reinforcement learning techniques
Akash Kundu, Przemysław Bedełek, Mateusz Ostaszewski +4
The variational quantum algorithms are crucial for the application of NISQ computers. Such algorithms require short quantum circuits, which are more amenable to implementation on n…
The Tunnel Effect: Building Data Representations in Deep Neural Networks
Wojciech Masarczyk, Mateusz Ostaszewski, Ehsan Imani +3
Deep neural networks are widely known for their remarkable effectiveness across various tasks, with the consensus that deeper networks implicitly learn more complex data representa…