1 citations · 1 across the 2 of their papers we have counts for
4 papers
HyConEx: Hypernetwork classifier with counterfactual explanations for tabular data
Patryk MarszaÅek, Kamil KsiÄ Å¼ek, 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…
CounterFlowNet: From Minimal Changes to Meaningful Counterfactual Explanations
Oleksii Furman, Patryk MarszaÅek, Jan MasÅowski +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…
OBSR: Open Benchmark for Spatial Representations
Julia Moska, Oleksii Furman, Kacper Kozaczko +4
GeoAI is evolving rapidly, fueled by diverse geospatial datasets like traffic patterns, environmental data, and crowdsourced OpenStreetMap (OSM) information. While sophisticated AI…