most citedMitigating Dimensionality in 2D Rectangle Packing Problem under Reinforcement Learning Schema

3 citations · 3 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Explaining Similarity in Vision-Language Encoders with Weighted Banzhaf Interactions

Hubert Baniecki, Maximilian Muschalik, Fabian Fumagalli +3

Language-image pre-training (LIP) enables the development of vision-language models capable of zero-shot classification, localization, multimodal retrieval, and semantic understand…

eess.IV2025

X-ray transferable polyrepresentation learning

Weronika Hryniewska-Guzik, Przemyslaw Biecek

The success of machine learning algorithms is inherently related to the extraction of meaningful features, as they play a pivotal role in the performance of these algorithms. Centr…

cs.NE2024

Cartesian Genetic Programming Approach for Designing Convolutional Neural Networks

Maciej Krzywda, Szymon Łukasik, Amir Gandomi H

The present study covers an approach to neural architecture search (NAS) using Cartesian genetic programming (CGP) for the design and optimization of Convolutional Neural Networks…

cs.DM2024

Task scheduling for autonomous vehicles in the Martian environment

Wojciech Burzyński, Mariusz Kaleta

In the paper, we introduced a novel variant of Electric VRP/TSP, the Solar Powered Rover Routing Problem (SPRRP), to tackle the routing of energy-constrained autonomous electric ve…

cs.LG20243 cited

Mitigating Dimensionality in 2D Rectangle Packing Problem under Reinforcement Learning Schema

Waldemar Kołodziejczyk, Mariusz Kaleta

This paper explores the application of Reinforcement Learning (RL) to the two-dimensional rectangular packing problem. We propose a reduced representation of the state and action s…