1 code implementation • 31 Oct 2023 • Hardik Rajpal, Clem von Stengel, Pedro A. M. Mediano, Fernando E. Rosas, Eduardo Viegas, Pablo A. Marquet, Henrik J. Jensen
At what level does selective pressure effectively act?
1 code implementation • 10 Aug 2023 • Andrea I Luppi, Fernando E. Rosas, Gustavo Deco, Morten L. Kringelbach, Pedro A. M. Mediano
Temporal irreversibility, often referred to as the arrow of time, is a fundamental concept in statistical mechanics.
1 code implementation • NeurIPS 2023 • Zhaolu Liu, Robert L. Peach, Pedro A. M. Mediano, Mauricio Barahona
Models that rely solely on pairwise relationships often fail to capture the complete statistical structure of the complex multivariate data found in diverse domains, such as socio-economic, ecological, or biomedical systems.
1 code implementation • 8 Mar 2023 • Fernando E. Rosas, Diego Candia-Rivera, Andrea I Luppi, Yike Guo, Pedro A. M. Mediano
Recent research is revealing how cognitive processes are supported by a complex interplay between the brain and the rest of the body, which can be investigated by the analysis of physiological features such as breathing rhythms, heart rate, and skin conductance.
no code implementations • 6 Oct 2022 • Alexandra M. Proca, Fernando E. Rosas, Andrea I. Luppi, Daniel Bor, Matthew Crosby, Pedro A. M. Mediano
These findings open the door to new ways of investigating how and why learning systems employ specific information-processing strategies, and support the principle that the capacity for general-purpose learning critically relies in the system's information dynamics.
no code implementations • 12 Nov 2021 • Pedro A. M. Mediano, Fernando E. Rosas, Andrea I. Luppi, Henrik J. Jensen, Anil K. Seth, Adam B. Barrett, Robin L. Carhart-Harris, Daniel Bor
Emergence is a profound subject that straddles many scientific disciplines, including the formation of galaxies and how consciousness arises from the collective activity of neurons.
no code implementations • 27 Sep 2021 • Pedro A. M. Mediano, Fernando E. Rosas, Andrea I Luppi, Robin L. Carhart-Harris, Daniel Bor, Anil K. Seth, Adam B. Barrett
Complex systems, from the human brain to the global economy, are made of multiple elements that interact in such ways that the behaviour of the `whole' often seems to be more than what is readily explainable in terms of the `sum of the parts.'
no code implementations • 18 Jun 2021 • Pedro A. M. Mediano, Fernando E. Rosas, Juan Carlos Farah, Murray Shanahan, Daniel Bor, Adam B. Barrett
The apparent dichotomy between information-processing and dynamical approaches to complexity science forces researchers to choose between two diverging sets of tools and explanations, creating conflict and often hindering scientific progress.
no code implementations • 14 Oct 2020 • Fernando E. Rosas, Pedro A. M. Mediano, Michael Gastpar
Learning and compression are driven by the common aim of identifying and exploiting statistical regularities in data, which opens the door for fertile collaboration between these areas.
no code implementations • 28 Aug 2020 • Fernando E. Rosas, Pedro A. M. Mediano, Martin Biehl, Shamil Chandaria, Daniel Polani
We introduce a novel framework to identify perception-action loops (PALOs) directly from data based on the principles of computational mechanics.
1 code implementation • NeurIPS 2020 • Zafeirios Fountas, Noor Sajid, Pedro A. M. Mediano, Karl Friston
In a more complex Animal-AI environment, our agents (using the same neural architecture) are able to simulate future state transitions and actions (i. e., plan), to evince reward-directed navigation - despite temporary suspension of visual input.
1 code implementation • 17 Apr 2020 • Fernando E. Rosas, Pedro A. M. Mediano, Henrik J. Jensen, Anil. K. Seth, Adam B. Barrett, Robin L. Carhart-Harris, Daniel Bor
The broad concept of emergence is instrumental in various of the most challenging open scientific questions -- yet, few quantitative theories of what constitutes emergent phenomena have been proposed.
1 code implementation • 5 Sep 2019 • Pedro A. M. Mediano, Fernando Rosas, Robin L. Carhart-Harris, Anil. K. Seth, Adam B. Barrett
Most information dynamics and statistical causal analysis frameworks rely on the common intuition that causal interactions are intrinsically pairwise -- every 'cause' variable has an associated 'effect' variable, so that a 'causal arrow' can be drawn between them.
Neurons and Cognition Data Analysis, Statistics and Probability
no code implementations • ICLR 2019 • Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano, Vinicius Zambaldi, Neil C. Rabinowitz, Thore Graepel, Matthew Botvinick, Peter W. Battaglia
The behavioral dynamics of multi-agent systems have a rich and orderly structure, which can be leveraged to understand these systems, and to improve how artificial agents learn to operate in them.
no code implementations • 5 Jul 2017 • Xerxes D. Arsiwalla, Pedro A. M. Mediano, Paul F. M. J. Verschure
Recent complexity measures such as integrated information have sought to operationalize this problem taking a whole-versus-parts perspective, wherein one explicitly computes the amount of information generated by a network as a whole over and above that generated by the sum of its parts during state transitions.
3 code implementations • 8 Nov 2016 • Nat Dilokthanakul, Pedro A. M. Mediano, Marta Garnelo, Matthew C. H. Lee, Hugh Salimbeni, Kai Arulkumaran, Murray Shanahan
We study a variant of the variational autoencoder model (VAE) with a Gaussian mixture as a prior distribution, with the goal of performing unsupervised clustering through deep generative models.
Ranked #7 on Human Pose Forecasting on HumanEva-I