no code implementations • 1 Mar 2024 • Michal Nauman, Mateusz Ostaszewski, Marek Cygan
VPL uses a small validation buffer to adjust the levels of pessimism throughout the agent training, with the pessimism set such that the approximation error of the critic targets is minimized.
no code implementations • 1 Mar 2024 • Michal Nauman, Michał Bortkiewicz, Mateusz Ostaszewski, Piotr Miłoś, Tomasz Trzciński, Marek Cygan
We tested these agents across 14 diverse tasks from 2 simulation benchmarks.
no code implementations • 5 Feb 2024 • Yash J. Patel, Akash Kundu, Mateusz Ostaszewski, Xavier Bonet-Monroig, Vedran Dunjko, Onur Danaci
In the case of parameter optimization alone, noise effects have been observed to dramatically influence the performance of the optimizer and final outcomes, which is a key line of study.
no code implementations • 5 Feb 2024 • Maciej Wołczyk, Bartłomiej Cupiał, Mateusz Ostaszewski, Michał Bortkiewicz, Michał Zając, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś
Fine-tuning is a widespread technique that allows practitioners to transfer pre-trained capabilities, as recently showcased by the successful applications of foundation models.
no code implementations • 30 Oct 2023 • Wojciech Masarczyk, Tomasz Trzciński, Mateusz Ostaszewski
In the era of transfer learning, training neural networks from scratch is becoming obsolete.
1 code implementation • 19 Jun 2023 • Akash Kundu, Przemysław Bedełek, Mateusz Ostaszewski, Onur Danaci, Yash J. Patel, Vedran Dunjko, Jarosław A. Miszczak
We demonstrate that the circuits proposed by the reinforcement learning methods are shallower than the standard variational quantum state diagonalization algorithm and thus can be used in situations where hardware capabilities limit the depth of quantum circuits.
2 code implementations • 29 Nov 2022 • Samuel Kessler, Mateusz Ostaszewski, Michał Bortkiewicz, Mateusz Żarski, Maciej Wołczyk, Jack Parker-Holder, Stephen J. Roberts, Piotr Miłoś
World models power some of the most efficient reinforcement learning algorithms.
no code implementations • 11 Nov 2022 • Michał Bortkiewicz, Jakub Łyskawa, Paweł Wawrzyński, Mateusz Ostaszewski, Artur Grudkowski, Tomasz Trzciński
In this paper, we address this gap in the state-of-the-art approaches and propose a method in which the validity of higher-level actions (thus lower-level goals) is constantly verified at the higher level.
Hierarchical Reinforcement Learning reinforcement-learning +1
no code implementations • 30 Jul 2022 • Paweł Wawrzyński, Wojciech Masarczyk, Mateusz Ostaszewski
To that end, the dispersion should be tuned to assure a sufficiently high probability (densities) of the actions in the replay buffer and the modes of the distributions that generated them, yet this dispersion should not be higher.
no code implementations • NeurIPS 2021 • Mateusz Ostaszewski, Lea M. Trenkwalder, Wojciech Masarczyk, Eleanor Scerri, Vedran Dunjko
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.
no code implementations • 12 Sep 2019 • Wojciech Masarczyk, Przemysław Głomb, Bartosz Grabowski, Mateusz Ostaszewski
This approach can be applied to many of the hyperspectral classification problems.
General Classification Hyperspectral Image Classification +2
no code implementations • 23 May 2019 • Mateusz Ostaszewski, Edward Grant, Marcello Benedetti
We demonstrate the method for optimizing a variational quantum eigensolver for finding the ground states of Lithium Hydride and the Heisenberg model in simulation, and for finding the ground state of Hydrogen gas on the IBM Melbourne quantum computer.
Quantum Physics
6 code implementations • 4 Jan 2018 • Adam Glos, Jarosław Adam Miszczak, Mateusz Ostaszewski
The presented paper describes QSWalk. jl package for Julia programming language, developed for the purpose of simulating the evolution of open quantum systems.
Quantum Physics
no code implementations • 2 Apr 2015 • Mateusz Ostaszewski, Przemysław Sadowski, Piotr Gawron
We present a novel quantum algorithm for classification of images.