Predicting Language Recovery after Stroke with Convolutional Networks on Stitched MRI. - Yusuf H. Roohani; Noor Sajid; Pranava Madhyastha; Cathy J. Price; Thomas M. H. Hope (CoRR, 2018)

Demystifying active inference. - Noor Sajid; Philip J. Ball; Karl J. Friston (CoRR, 2019)

Deep active inference agents using Monte-Carlo methods. - Zafeirios Fountas; Noor Sajid; Pedro A. M. Mediano; Karl J. Friston (NeurIPS, 2020)

The relationship between dynamic programming and active inference: the discrete, finite-horizon case. - Lancelot Da Costa; Noor Sajid; Thomas Parr; Karl J. Friston; Ryan Smith (CoRR, 2020)

Modules or Mean-Fields? - Thomas Parr; Noor Sajid; Karl J. Friston (Entropy, 2020)

Active Inference for Stochastic Control. - Aswin Paul; Noor Sajid; Manoj Gopalkrishnan; Adeel Razi (PKDD/ECML Workshops (1), 2021)

Exploration and preference satisfaction trade-off in reward-free learning. - Noor Sajid; Panagiotis Tigas; Alexey Zakharov; Zafeirios Fountas; Karl J. Friston (CoRR, 2021)

Active inference, Bayesian optimal design, and expected utility. - Noor Sajid; Lancelot Da Costa; Thomas Parr; Karl J. Friston (CoRR, 2021)

Cancer Niches and Their Kikuchi Free Energy. - Noor Sajid; Laura Convertino; Karl J. Friston (Entropy, 2021)

Generative Models for Active Vision. - Thomas Parr; Noor Sajid; Lancelot Da Costa; M. Berk Mirza; Karl J. Friston (Frontiers Neurorobotics, 2021)

Active Inference: Demystified and Compared. - Noor Sajid; Philip J. Ball; Thomas Parr; Karl J. Friston (Neural Comput., 2021)

Modelling non-reinforced preferences using selective attention. - Noor Sajid; Panagiotis Tigas; Zafeirios Fountas; Qinghai Guo; Alexey Zakharov; Lancelot Da Costa (CoRR, 2022)

How Active Inference Could Help Revolutionise Robotics. - Lancelot Da Costa; Pablo Lanillos; Noor Sajid; Karl J. Friston; Shujhat Khan (Entropy, 2022)

Bayesian Brains and the Rényi Divergence. - Noor Sajid; Francesco Faccio; Lancelot Da Costa; Thomas Parr; Jürgen Schmidhuber; Karl J. Friston (Neural Comput., 2022)

Reclaiming saliency: Rhythmic precision-modulated action and perception. - Ajith Anil Meera; Filip Novicky; Thomas Parr; Karl J. Friston; Pablo Lanillos; Noor Sajid (Frontiers Neurorobotics, 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)

Reward Maximization Through Discrete Active Inference. - Lancelot Da Costa; Noor Sajid; Thomas Parr; Karl J. Friston; Ryan Smith (Neural Comput., 2023)

Hierarchical generative modelling for autonomous robots. - Kai Yuan; Noor Sajid; Karl J. Friston; Zhibin Li 001 (Nat. Mac. Intell., 2023)

Learning Hierarchical World Models with Adaptive Temporal Abstractions from Discrete Latent Dynamics. - Christian Gumbsch; Noor Sajid; Georg Martius; Martin V. Butz (ICLR, 2024)

Active Inference as a Model of Agency. - Lancelot Da Costa; Samuel Tenka; Dominic Zhao; Noor Sajid (CoRR, 2024)

On efficient computation in active inference. - Aswin Paul; Noor Sajid; Lancelot Da Costa; Adeel Razi (Expert Syst. Appl., 2024)

A Broken Duet: Multistable Dynamics in Dyadic Interactions. - Johan Medrano; Noor Sajid (Entropy, 2024)

Model alignment using inter-modal bridges. - Ali Gholamzadeh; Noor Sajid (CoRR, 2025)

Dissociating model architectures from inference computations. - Noor Sajid; Johan Medrano (CoRR, 2025)