Sajid, Noor

Active inference on discrete state-spaces: A synthesis

Da Costa, L., Parr, T., Sajid, N., Veselic, S., Neacsu, V., & Friston, K. (2020) · Journal of Mathematical Psychology

Embodied and Extended CognitionCognitive Science and Education Research

Cited by 226

The free energy principle made simpler but not too simple

Friston, K., Da Costa, L., Sajid, N., Heins, C., Ueltzhöffer, K., Pavliotis, G. A., & Parr, T. (2023) · Physics Reports

Embodied and Extended CognitionPhilosophy of Biology and Scientific Explanation

Cited by 163

Deep active inference agents using Monte-Carlo methods

Fountas, Z., Sajid, N., Mediano, P. A. M., & Friston, K. (2020) · arXiv

Embodied and Extended CognitionReinforcement Learning in Robotics

Cited by 64

Degeneracy and Redundancy in Active Inference

Sajid, N., Parr, T., Hope, T. M., Price, C. J., & Friston, K. J. (2020) · Cerebral Cortex

Embodied and Extended CognitionBayesian Modeling and Causal Inference

Cited by 49

Generative models for active vision

Parr, T., Sajid, N., Da Costa, L., Mirza, M. B., & Friston, K. J. (2021) · Frontiers in Neurorobotics

Embodied and Extended CognitionVisual perception and processing mechanisms

Cited by 46

Reward maximization through discrete active inference

Da Costa, L., Sajid, N., Parr, T., Friston, K., & Smith, R. (2023) · Neural Computation

Embodied and Extended CognitionReinforcement Learning in Robotics

Cited by 35

Hierarchical generative modelling for autonomous robots

Yuan, K., Sajid, N., Friston, K., & Li, Z. (2023) · Nature Machine Intelligence

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 23

Exploration and preference satisfaction trade-off in reward-free learning

Sajid, N., Tigas, P., Zakharov, A., Fountas, Z., & Friston, K. (2021) · arXiv

Reinforcement Learning in RoboticsEmbodied and Extended Cognition

Cited by 11