Abstract Understanding the consequences of continued greenhouse‐gas emissions requires determining whether recent emissions can be robustly linked to changes in extreme weather events. However, current approaches have a limited ability to quantify changes in extreme weather caused by small subsets of anthropogenic emissions, particularly for individual events. To address these limitations, we train a generative machine‐learning model to predict spatially‐explicit changes in daily surface temperature at different levels of cumulative emissions, conditional on the event’s observed meteorological conditions. Using this approach, we find strong evidence (>95% probability) that the combined effects of anthropogenic emissions released since the 2015 UN Paris Agreement have increased the intensity of Europe’s summer temperature extremes since 2021. Additionally, our results suggest >99% probability that regional‐mean temperature during Europe’s high‐impact June 2025 heatwave would have been lower (median estimate of 0.34°C) if the same large‐scale meteorological conditions had occurred under 2015 levels of cumulative emissions.