Month: June 2019

Localist plasticity identified by mutual information

The issue of memory is difficult for standard neural network models. Ubiquitous synaptic plasticity introduces the problem of interference, which limits pattern recall and introduces conflation errors. We present a lognormal recurrent neural network, load patterns into it (MNIST), and test the resulting neural representation for information content by an output classifier. We identify neurons, which ‘compress’ the pattern information into their own adjacency network, and by stimulating these achieve recall. Learning is limited to intrinsic plasticity and output synapses of these pattern neurons (localist plasticity), which prevents interference.

Our first experiments show that this form of storage and recall is possible, with the caveat of a ‘lossy’ recall similar to human memory. Comparing our results with a standard Gaussian network model, we notice that this effect breaks down for the Gaussian model.


Localist plasticity identified by mutual information

Gabriele Scheler, Johann Schumann


Exploration of the chemical space and its three historical regimes

We found that the number of new chemical compounds has grown exponentially with a 4.4% annual production rate from 1800 to 2015 not even affected by World Wars. There are three distinct growth regimes: proto-organic, organic, and organometallic, with decreasing variability in the production of compounds over time. Contrary to the belief that organic synthesis developed only after 1828, synthesis had been a key provider of new compounds already at the beginning of the 19th century. By 1900, it became the established tool to report new compounds. We found that chemists are conservative when selecting starting materials and that despite the growing production of new compounds, most of them belong to a restricted set of chemical compositions.


Exploration of the chemical space and its three historical regimes

Eugenio J. Llanos, Wilmer Leal, Duc H. Luu, Jürgen Jost, Peter F. Stadler, and Guillermo Restrepo


Quantifying the sensing power of vehicle fleets

Attaching sensors to crowd-sourced vehicles could provide a cheap and accurate way to monitor air pollution, road quality, and other aspects of a city’s health. But in order for so-called drive-by sensing to be practically useful, the sensor-equipped vehicle fleet needs to have large “sensing power”—that is, it needs to cover a large fraction of a city’s area during a given reference period. Here, we provide an analytic description of the sensing power of taxi fleets, which agrees with empirical data from nine major cities. Our results show taxis’ sensing power is unexpectedly large—in Manhattan; just 10 random taxis cover one-third of street segments daily, which certifies that drive-by sensing can be readily implemented in the real world.


Quantifying the sensing power of vehicle fleets
Kevin P. O’Keeffe, Amin Anjomshoaa, Steven H. Strogatz, Paolo Santi, and Carlo Ratti


Postgraduate School of Thinking, Vrije Universiteit Brussel

At the most fundamental level many of the problems we face are the unfortunate outcome of the malpractice of thinking. Whichever complex problem one may consider –be it ecological, societal, political, economic, organisational etc.– one will likely find that it is caused by the clashing of incompatible or inadequate manners of thinking. Even when these are genuinely well intended and strongly self-justified, they often inadvertently contribute to composite problematics.
The inadequacies of our thinking are deeply entrenched in the way that we humans, perceive the world, ourselves in the world, and how we interact with it. Our professional, educational, cultural and metaphysical systems strongly dispose us towards outlining sharp boundaries, separating objects from backgrounds, ’us’ from ‘them’, defining identities and curving out what is to be of significance from what can be dismissed, disposed of, or exploited. Such dispositions result in oversimplifications which are often apparent to us in the thinking of others, but much less in our own thinking. Yet, they are omnipresent and almost impossible to avoid. Once cohered by logical reasoning, anchored in captivating symbolism and encoded in algorithms, such simplifications turn into cages: mental, emotional, operational… Moving beyond them becomes literally unthinkable. We may repeat the mantra of ‘thinking outside the box’, we may praise critical, independent, creative and disruptive thinking, but these get deployed only in as far as they prove usable for the affirmation of our respective, deeply rooted worldviews.


Call for Applications: Cátedra Germinal Cocho en Ciencias de la Complejidad (Senior posdoc)

The Center for Complexity Sciences (C3) at the Universidad Nacional Autónoma de México is seeking candidates for a one year researcher position (extensible for a second year).


The candidates should have more than ten publications in indexed journals and to have directed at least one thesis (doctorate, masters, or bachelors). Projects can be individual or related to current research at the C3.