Realising Active Inference in Variational Message Passing: the Outcome-blind Certainty Seeker. - Théophile Champion; Marek Grzes; Howard Bowman (CoRR, 2021)

Realizing Active Inference in Variational Message Passing: The Outcome-Blind Certainty Seeker. - Théophile Champion; Marek Grzes; Howard Bowman (Neural Comput., 2021)

Multi-Modal and Multi-Factor Branching Time Active Inference. - Théophile Champion; Marek Grzes; Howard Bowman (CoRR, 2022)

Branching Time Active Inference with Bayesian Filtering. - Théophile Champion; Marek Grzes; Howard Bowman (Neural Comput., 2022)

Branching time active inference: Empirical study and complexity class analysis. - Théophile Champion; Howard Bowman; Marek Grzes (Neural Networks, 2022)

Branching Time Active Inference: The theory and its generality. - Théophile Champion; Lancelot Da Costa; Howard Bowman; Marek Grzes (Neural Networks, 2022)

Deconstructing deep active inference. - Théophile Champion; Marek Grzes; Lisa Bonheme; Howard Bowman (CoRR, 2023)

Reframing the Expected Free Energy: Four Formulations and a Unification. - Théophile Champion; Howard Bowman; Dimitrije Markovic; Marek Grzes (CoRR, 2024)

Structure learning with Temporal Gaussian Mixture for model-based Reinforcement Learning. - Théophile Champion; Marek Grzes; Howard Bowman (CoRR, 2024)

Deconstructing Deep Active Inference: A Contrarian Information Gatherer. - Théophile Champion; Marek Grzes; Lisa Bonheme; Howard Bowman (Neural Comput., 2024)