1 citations · 1 across the 3 of their papers we have counts for
4 papers
TACTIC for Navigating the Unknown: Tabular Anomaly deteCTion via In-Context inference
Patryk Marszałek, Tomasz Kuśmierczyk, Marek Śmieja
Anomaly detection for tabular data has been a long-standing unsupervised learning problem that remains a major challenge for current deep learning models. Recently, in-context lear…
CounterFlowNet: From Minimal Changes to Meaningful Counterfactual Explanations
Oleksii Furman, Patryk Marszałek, Jan Masłowski +3
Counterfactual explanations (CFs) provide human-interpretable insights into model's predictions by identifying minimal changes to input features that would alter the model's output…
DiCoFlex: Model-agnostic diverse counterfactuals with flexible control
Oleksii Furman, Ulvi Movsum-zada, Patryk Marszalek +2
Counterfactual explanations play a pivotal role in explainable artificial intelligence (XAI) by offering intuitive, human-understandable alternatives that elucidate machine learnin…
HyConEx: Hypernetwork classifier with counterfactual explanations for tabular data
Patryk Marszałek, Kamil Książek, Oleksii Furman +3
In recent years, there has been a growing interest in explainable AI methods. In addition to making accurate predictions, we also want to understand what the model's decision is ba…