Scaling Active Inference. - Alexander Tschantz; Manuel Baltieri; Anil K. Seth; Christopher L. Buckley (IJCNN, 2020)

Sophisticated Affective Inference: Simulating Anticipatory Affective Dynamics of Imagining Future Events. - Casper Hesp; Alexander Tschantz; Beren Millidge; Maxwell Ramstead; Karl J. Friston; Ryan Smith (IWAI, 2020)

On the Relationship Between Active Inference and Control as Inference. - Beren Millidge; Alexander Tschantz; Anil K. Seth; Christopher L. Buckley (IWAI, 2020)

Reinforcement Learning through Active Inference. - Alexander Tschantz; Beren Millidge; Anil K. Seth; Christopher L. Buckley (CoRR, 2020)

Reinforcement Learning as Iterative and Amortised Inference. - Beren Millidge; Alexander Tschantz; Anil K. Seth; Christopher L. Buckley (CoRR, 2020)

Control as Hybrid Inference. - Alexander Tschantz; Beren Millidge; Anil K. Seth; Christopher L. Buckley (CoRR, 2020)

Activation Relaxation: A Local Dynamical Approximation to Backpropagation in the Brain. - Beren Millidge; Alexander Tschantz; Anil K. Seth; Christopher L. Buckley (CoRR, 2020)

Relaxing the Constraints on Predictive Coding Models. - Beren Millidge; Alexander Tschantz; Anil K. Seth; Christopher L. Buckley (CoRR, 2020)

Investigating the Scalability and Biological Plausibility of the Activation Relaxation Algorithm. - Beren Millidge; Alexander Tschantz; Anil K. Seth; Christopher L. Buckley (CoRR, 2020)

Learning action-oriented models through active inference. - Alexander Tschantz; Anil K. Seth; Christopher L. Buckley (PLoS Comput. Biol., 2020)

Neural Kalman Filtering. - Beren Millidge; Alexander Tschantz; Anil K. Seth; Christopher L. Buckley (CoRR, 2021)

Understanding the origin of information-seeking exploration in probabilistic objectives for control. - Beren Millidge; Alexander Tschantz; Anil K. Seth; Christopher L. Buckley (CoRR, 2021)

Active Inference in Robotics and Artificial Agents: Survey and Challenges. - Pablo Lanillos; Cristian Meo; Corrado Pezzato; Ajith Anil Meera; Mohamed Baioumy; Wataru Ohata; Alexander Tschantz; Beren Millidge; Martijn Wisse; Christopher L. Buckley; Jun Tani (CoRR, 2021)

The Acquisition of Culturally Patterned Attention Styles Under Active Inference. - Axel Constant; Alexander Tschantz; Beren Millidge; Felipe Criado-Boado; Luis M. Martinez; Johannes Müller; Andy Clark (Frontiers Neurorobotics, 2021)

Whence the Expected Free Energy? - Beren Millidge; Alexander Tschantz; Christopher L. Buckley (Neural Comput., 2021)

Capsule Networks as Generative Models. - Alex B. Kiefer; Beren Millidge; Alexander Tschantz; Christopher L. Buckley (IWAI, 2022)

Hybrid Predictive Coding: Inferring, Fast and Slow. - Alexander Tschantz; Beren Millidge; Anil K. Seth; Christopher L. Buckley (CoRR, 2022)

Designing Ecosystems of Intelligence from First Principles. - Karl J. Friston; Maxwell J. D. Ramstead; Alex B. Kiefer; Alexander Tschantz; Christopher L. Buckley; Mahault Albarracin; Riddhi J. Pitliya; Conor Heins; Brennan Klein; Beren Millidge; Dalton A. R. Sakthivadivel; Toby St Clere Smithe; et al. (CoRR, 2022)

pymdp: A Python library for active inference in discrete state spaces. - Conor Heins; Beren Millidge; Daphne Demekas; Brennan Klein; Karl J. Friston; Iain D. Couzin; Alexander Tschantz (J. Open Source Softw., 2022)

Predictive Coding Approximates Backprop Along Arbitrary Computation Graphs. - Beren Millidge; Alexander Tschantz; Christopher L. Buckley (Neural Comput., 2022)

Supervised structure learning. - Karl J. Friston; Lancelot Da Costa; Alexander Tschantz; Alex B. Kiefer; Tommaso Salvatori; Victorita Neacsu; Magnus T. Koudahl; Conor Heins; Noor Sajid; Dimitrije Markovic; Thomas Parr; Tim Verbelen; et al. (CoRR, 2023)

Active Inference and Intentional Behaviour. - Karl J. Friston; Tommaso Salvatori; Takuya Isomura; Alexander Tschantz; Alex B. Kiefer; Tim Verbelen; Magnus T. Koudahl; Aswin Paul; Thomas Parr; Adeel Razi; Brett J. Kagan; Christopher L. Buckley; et al. (CoRR, 2023)

From pixels to planning: scale-free active inference. - Karl J. Friston; Conor Heins; Tim Verbelen; Lancelot Da Costa; Tommaso Salvatori; Dimitrije Markovic; Alexander Tschantz; Magnus T. Koudahl; Christopher Buckley 001; Thomas Parr (CoRR, 2024)

Gradient-free variational learning with conditional mixture networks. - Conor Heins; Hao Wu; Dimitrije Markovic; Alexander Tschantz; Jeff Beck; Christopher Buckley 001 (CoRR, 2024)

Variational Bayes Gaussian Splatting. - Toon Van de Maele; Ozan Çatal; Alexander Tschantz; Christopher L. Buckley; Tim Verbelen (CoRR, 2024)

Navigation under uncertainty: Trajectory prediction and occlusion reasoning with switching dynamical systems. - Ran Wei; Joseph Lee; Shohei Wakayama; Alexander Tschantz; Conor Heins; Christopher Buckley 001; John Carenbauer; Hari Thiruvengada; Mahault Albarracin; Miguel de Prado; Petter Horling; Peter Winzell; et al. (CoRR, 2024)

Natural Induction: Spontaneous Adaptive Organisation without Natural Selection. - Christopher L. Buckley; Tim Lewens; Michael Levin 001; Beren Millidge; Alexander Tschantz; Richard A. Watson (Entropy, 2024)

Active Inference and Intentional Behavior. - Karl J. Friston; Tommaso Salvatori; Takuya Isomura; Alexander Tschantz; Alex B. Kiefer; Tim Verbelen; Magnus T. Koudahl; Aswin Paul; Thomas Parr; Adeel Razi; Brett J. Kagan; Christopher L. Buckley; et al. (Neural Comput., 2025)

Bayesian Predictive Coding. - Alexander Tschantz; Magnus T. Koudahl; Hampus Linander; Lancelot Da Costa; Conor Heins; Jeff Beck; Christopher L. Buckley (CoRR, 2025)

AXIOM: Learning to Play Games in Minutes with Expanding Object-Centric Models. - Conor Heins; Toon Van de Maele; Alexander Tschantz; Hampus Linander; Dimitrije Markovic; Tommaso Salvatori; Corrado Pezzato; Ozan Çatal; Ran Wei; Magnus T. Koudahl; Marco Perin; Karl J. Friston; et al. (CoRR, 2025)