I'm delighted that Excel now supports first-class, lexically scoped lambda-expressions. Excel just became a Turing-complete programming language!
https://t.co/DNWmMN6g6b
Nice media coverage of our recent paper by @scienceceals: Machine learning helps retrace evolution of classical music https://t.co/OYjRd7xB4c #epfl#musicscience
Our paper ‘Age-dependent statistical learning trajectories reveal differences in information weighting' is now online. We show differences in how younger and older adults sample information and deal with uncertainty. @EPFL_en@MARCSInstitute@APA_Journals https://t.co/RxTVMktlwD
📢Looking for a PhD position? Have strong mathematical skills? Fascinated by fundamental research? Keen to work in an interdisciplinary setting interfacing theoretical neuroscience, Bayesian modeling, philosophy and cognitive science? This PhD position may be for you! 👇
During the pandemic, classical musicians and orchestras are reliant on streaming their performances to maintain their profile and solicit donations. That's a problem, because the platforms' copyright bots HATE classical music.
https://t.co/2OmKjDDgfQ
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I'm having trouble concentrating on science animations right now, so instead here are some screenshots from my favourite document on the planet.
These are taken from a 'work in progress' document from Pepsi's 2008 rebrand. Every figure is as incomprehensible as this one. 1/23
Hi, I'm a CS PhD candidate at Indiana University studying programming languages and compilers under Ryan Newton, and I'm looking for a postdoc/research position starting Fall of this year.
My CV and contact info: https://t.co/3JkHTR79bE
Please share/forward if you can, thanks!
Probably the most exciting #musicscience paper I've read this year: The Rapid Emergence of Musical Pitch Structure in Human Cortex https://t.co/dNZi9jJz5z Chapeau @thomps95 & colleagues
@BartoszMilewski@johncarlosbaez@YistvanPof MT is a lot about describing this shared knowledge (chords, scales, etc), but it's not very good at explaining how listeners' perceptions come about, which is a cognitive question. Instead it relies on everybody having similar perceptions, which is why analysis seems arbitrary.
@BartoszMilewski@johncarlosbaez@YistvanPof One way to look at MT/analysis is that it doesn't describe the music itself but the listener's perception of it and their interpretation of the composers intentions. So it's inherently ambiguous and relies on lots of shared cultural (implicit) knowledge.
@BartoszMilewski@johncarlosbaez@YistvanPof Possible bases for non-equiv pitch space are
- octaves x fifths
- diatonic steps x alterations
- chromatic x diatonic semitones
- etc.
@BartoszMilewski@johncarlosbaez@YistvanPof This is interestingly not just a notational issue. If B# and C are different notes, pitch space becomes (at least) 2 dimensional. Enharmonic equivalence maps back into 1 dim. Similarly, ignoring octaves, you either get a circle (enh. eqiv.) or a line (non-eqiv) of fifths.
DEADLINE EXTENSION
Dear colleagues, due to the current situation leading to an increased workload for many of us, we have decided to extend the deadline for submissions for the EMR Special Issue on "Open Science in Musicology" to 30 April 2020. Please share widely! #musicscience