Noor Sajid | DeepAI

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Featured Co-authors

Jürgen Schmidhuber
84 publications
Zhibin Li
61 publications
Pranava Madhyastha
32 publications
Karl Friston
24 publications
Pablo Lanillos
23 publications
Pedro A. M. Mediano
15 publications
Kai Yuan
15 publications
Qinghai Guo
14 publications
Philip J. Ball
11 publications
Zafeirios Fountas
11 publications
Panagiotis Tigas
10 publications

∙ 08/15/2023

Hierarchical generative modelling for autonomous robots

Humans can produce complex whole-body motions when interacting with thei...

0 Kai Yuan, et al. ∙

∙ 07/02/2023

On efficient computation in active inference

Despite being recognized as neurobiologically plausible, active inferenc...

0 Aswin Paul, et al. ∙

∙ 07/25/2022

Modelling non-reinforced preferences using selective attention

How can artificial agents learn non-reinforced preferences to continuous...

4 Noor Sajid, et al. ∙

∙ 03/23/2022

Reclaiming saliency: rhythmic precision-modulated action and perception

Computational models of visual attention in artificial intelligence and ...

0 Ajith Anil Meera, et al. ∙

∙ 09/21/2021

Active inference, Bayesian optimal design, and expected utility

Active inference, a corollary of the free energy principle, is a formal ...

0 Noor Sajid, et al. ∙

∙ 08/27/2021

Active Inference for Stochastic Control

Active inference has emerged as an alternative approach to control probl...

13 Aswin Paul, et al. ∙

∙ 07/12/2021

Bayesian brains and the Rényi divergence

Under the Bayesian brain hypothesis, behavioural variations can be attri...

8 Noor Sajid, et al. ∙

∙ 06/08/2021

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

Biological agents have meaningful interactions with their environment de...

6 Noor Sajid, et al. ∙

∙ 09/17/2020

The relationship between dynamic programming and active inference: the discrete, finite-horizon case

Active inference is a normative framework for generating behaviour based...

18 Lancelot Da Costa, et al. ∙

∙ 06/07/2020

Deep active inference agents using Monte-Carlo methods

Active inference is a Bayesian framework for understanding biological in...

15 Zafeirios Fountas, et al. ∙

∙ 09/24/2019

Demystifying active inference

Active inference is a first (Bayesian) principles account of how autonom...

0 Noor Sajid, et al. ∙

∙ 11/26/2018

Predicting Language Recovery after Stroke with Convolutional Networks on Stitched MRI

One third of stroke survivors have language difficulties. Emerging evide...

0 Yusuf H. Roohani, et al. ∙

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