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07/27/2023
Collective behavior from surprise minimization
Collective motion is ubiquitous in nature; groups of animals, such as fi...
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06/27/2023
Causal Inference via Predictive Coding
Bayesian and causal inference are fundamental processes for intelligence...
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12/02/2022
Designing Ecosystems of Intelligence from First Principles
This white paper lays out a vision of research and development in the fi...
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11/22/2022
Interpreting Neural Networks through the Polytope Lens
Mechanistic interpretability aims to explain what a neural network has l...
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08/15/2022
Preventing Deterioration of Classification Accuracy in Predictive Coding Networks
Predictive Coding Networks (PCNs) aim to learn a generative model of the...
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07/20/2022
Successor Representation Active Inference
Recent work has uncovered close links between between classical reinforc...
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06/01/2022
A Theoretical Framework for Inference Learning
Backpropagation (BP) is the most successful and widely used algorithm in...
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04/05/2022
Hybrid Predictive Coding: Inferring, Fast and Slow
Predictive coding is an influential model of cortical neural activity. I...
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01/11/2022
pymdp: A Python library for active inference in discrete state spaces
Active inference is an account of cognition and behavior in complex syst...
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12/03/2021
Active Inference in Robotics and Artificial Agents: Survey and Challenges
Active inference is a mathematical framework which originated in computa...
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09/02/2021
Habitual and Reflective Control in Hierarchical Predictive Coding
In cognitive science, behaviour is often separated into two types. Refle...
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08/30/2021
A Mathematical Walkthrough and Discussion of the Free Energy Principle
The Free-Energy-Principle (FEP) is an influential and controversial theo...
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07/27/2021
Predictive Coding: a Theoretical and Experimental Review
Predictive coding offers a potentially unifying account of cortical func...
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06/30/2021
Applications of the Free Energy Principle to Machine Learning and Neuroscience
In this PhD thesis, we explore and apply methods inspired by the free en...
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06/04/2021
Online reinforcement learning with sparse rewards through an active inference capsule
Intelligent agents must pursue their goals in complex environments with ...
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06/03/2021
Towards a Mathematical Theory of Abstraction
While the utility of well-chosen abstractions for understanding and pred...
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03/11/2021
Understanding the origin of information-seeking exploration in probabilistic objectives for control
The exploration-exploitation trade-off is central to the description of ...
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02/19/2021
Neural Kalman Filtering
The Kalman filter is a fundamental filtering algorithm that fuses noisy ...
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10/13/2020
Investigating the Scalability and Biological Plausibility of the Activation Relaxation Algorithm
The recently proposed Activation Relaxation (AR) algorithm provides a si...
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10/02/2020
Relaxing the Constraints on Predictive Coding Models
Predictive coding is an influential theory of cortical function which po...
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09/11/2020
Activation Relaxation: A Local Dynamical Approximation to Backpropagation in the Brain
The backpropagation of error algorithm (backprop) has been instrumental ...
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07/11/2020
Control as Hybrid Inference
The field of reinforcement learning can be split into model-based and mo...
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06/23/2020
On the Relationship Between Active Inference and Control as Inference
Active Inference (AIF) is an emerging framework in the brain sciences wh...
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06/13/2020
Reinforcement Learning as Iterative and Amortised Inference
There are several ways to categorise reinforcement learning (RL) algorit...
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06/07/2020
Predictive Coding Approximates Backprop along Arbitrary Computation Graphs
Backpropagation of error (backprop) is a powerful algorithm for training...
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04/17/2020
Whence the Expected Free Energy?
The Expected Free Energy (EFE) is a central quantity in the theory of ac...
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02/28/2020
Reinforcement Learning through Active Inference
The central tenet of reinforcement learning (RL) is that agents seek to ...
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07/08/2019