Through Information Reconciliation, two legitimate parties of Channel Reciprocity-based Key Generation assure that they extract the same key from local channel measurements. Current protocols exchange messages: Interactivity both causes delays and energy expenditure, and leaks information about the keying material to adversaries.We suggest non-interactive reconciliation, using a Siamese Network of CNNs that extracts reciprocal and suppresses nonreciprocal components in the measurements. Training and evaluating on real-world and synthetic data, we demonstrate that it blindly achieves higher correlation of the outputs at legitimate parties than the interactive state of the art, thus eliminating cost and information leakage at superior performance.