In this paper, we develop a reliable bandwidth-efficient solution for coherent reception in networks prone to self-interference. Our primary focus is on OFDM-based amplify-and-forward two-way relaying, where each source node suffers from re-radiation of its own signal. An important issue is the superposition of the desired and interfering signals, which makes the channel estimation task difficult, especially for varying channel coefficients. To address this challenging problem, we introduce a factor-graph model of the estimation and detection problem at hand. Exploiting the conditional independence between unknown variables in the factor-graph, an efficient message-passing algorithm, that performs joint Bayesian channel estimation, self-interference mitigation and decoding, is derived. Simulation results show that the performance of the proposed method is close to that given by perfect knowledge of the channel for the target and interfering signals, even with limited training overhead