3 citations · 16 across the 13 of their papers we have counts for
13 papers
COGENT: Counterfactual Gaussian Explanations for Volumetric Medical Images
Dorian Rząsa, Bartosz Zabdyr, Krzysztof Piekarz +7
Explainability is essential for deploying deep learning models in high-stakes medical applications. Existing explainability methods for volumetric imaging predominantly operate in…
Explaining BiomedCLIP with Weighted Banzhaf Interactions Supported by Tree-Gram Parsing
Jakub Rymarski, Adam Rempała, Bartłomiej Sobieski +1
Vision-Language Models (VLMs) are demonstrating significant capabilities in medical tasks like radiology analysis, yet providing faithful and interpretable explanations remains a k…
Local Intrinsic Dimension Unveils Hallucinations in Diffusion Models
Bartlomiej Sobieski, Matthew Tivnan, Dawid Płudowski +4
Diffusion models are prone to generating structural hallucinations - samples that match the statistical properties of the training data yet defy underlying structural rules, result…
Auditing Sybil: Explaining Deep Lung Cancer Risk Prediction Through Generative Interventional Attributions
Bartlomiej Sobieski, Jakub Grzywaczewski, Karol Dobiczek +6
Lung cancer remains the leading cause of cancer mortality, driving the development of automated screening tools to alleviate radiologist workload. Standing at the frontier of this…
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…
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…
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…
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…
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…
Swin SMT: Global Sequential Modeling in 3D Medical Image Segmentation
Szymon Płotka, Maciej Chrabaszcz, Przemyslaw Biecek
Recent advances in Vision Transformers (ViTs) have significantly enhanced medical image segmentation by facilitating the learning of global relationships. However, these methods fa…
Rico: extended TIAGo robot towards up-to-date social and assistive robot usage scenarios
Tomasz Winiarski, Wojciech Dudek, Daniel Giełdowski
Social and assistive robotics have vastly increased in popularity in recent years. Due to the wide range of usage, robots executing such tasks must be highly reliable and possess e…
Aggregated Attributions for Explanatory Analysis of 3D Segmentation Models
Maciej Chrabaszcz, Hubert Baniecki, Piotr Komorowski +2
Analysis of 3D segmentation models, especially in the context of medical imaging, is often limited to segmentation performance metrics that overlook the crucial aspect of explainab…
A comparative analysis of deep learning models for lung segmentation on X-ray images
Weronika Hryniewska-Guzik, Jakub Bilski, Bartosz Chrostowski +2
Robust and highly accurate lung segmentation in X-rays is crucial in medical imaging. This study evaluates deep learning solutions for this task, ranking existing methods and analy…