[PhilPhys] Center Fellows present talks - Frédéric Jaëck - Feb. 28 and Aliya Rumana -March 11th

[Center for Phil Sci]

The Center for Philosophy of Science invites you to join us for
our Lunch Time Talks.  Attend in person, Room 1117 on the 11th floor of the
Cathedral of Learning at the University of Pittsburgh or visit our live
stream on YouTube at *https://www.youtube.com/channel/UCrRp47ZMXD7NXO3a9Gyh2sg
<https://www.youtube.com/channel/UCrRp47ZMXD7NXO3a9Gyh2sg>*.

The upcoming talks are presented by The Center for Philosophy of Science's
 Visiting Fellow, Frédéric Jaëck and Postdoctoral Fellow,  Aliya Rumana. If
you would like information about these positions for the 2026-2027 academic
year, please see the bottom of this notice.

*Lunch Time Talk -  Frédéric Jaëck*

*Friday, February 28th @ 12:00 pm - 1:30 pm EDT*
If you are unable to join us in person at 1117 Cathedral of Learning
(11th Floor), use this link to follow along:
*https://pitt.zoom.us/j/94457810768
<https://pitt.zoom.us/j/94457810768>*

*Title: What is called ‘thinking’ in mathematics?*
*Abstract:*  The starting point of this talk will be the existence of a
dual mode of thinking in mathematics: one that allows us to manipulate
objects according to rules and a game that are co-constructed, and another,
more progressive mode, where the structure dictated by the rules and the
game gives way to much more diffuse and tangled connections.
I will show that these two modes of thinking are in constant and reciprocal
contamination, shaping how mathematicians exercise their force of thought.
This interplay also reveals a certain depth that always accompanies
mathematical propositions, resisting a flat logical interpretation and
offering insight into the very nature of mathematical thinking.


*SPRING BREAK - MARCH 3 -7*


*Lunch Time Talk -  Aliya Rumana*
*Tuesday, March 11th @ 12:00 pm - 1:30 pm EDT*
Can’t make it in-person? This talk will be available online through the
following:  Zoom – *https://pitt.zoom.us/j/96457118345
<https://pitt.zoom.us/j/96457118345>*

Title: A deflationary account of DCNN-based models in visual neuroscience
Abstract: Deep convolutional neural networks (DCNNs) have achieved
extraordinary accuracy at predicting electrophysiological data in the
ventral visual stream (VVS). What explains these predictive successes?
According to Cao & Yamins (2024), these models are so predictively
successful because (a) they near-optimally perform the same tasks as the
VVS (e.g., image classification) and (b) they perform these tasks in the
same kind of way due to their shared mechanistic structure. For the latter
reason, DCNNs are often touted as mechanistic models of the VVS. In this
presentation, I’ll argue that a weaker version of the first reason is
sufficient: these models are so predictively successful just because they
near-optimally perform proper parts (approximately half) of the tasks that
the VVS performs—not because they share any mechanistic structure. Any
structural similarities between DCNNs and the VVS is incidental to their
predictive success, so I conclude that DCNNs do not provide plausible
mechanistic models of the VVS.


*Information about 2026 - 2027 Fellowships*
 If you would like information about our Fellowships please visit our
websites. Applications will open late Fall.

*Postdoctoral Fellowships: *
https://www.centerphilsci.pitt.edu/programs/postdoc-fellowships/program-overview/

*Visiting Fellows Program:*
https://www.centerphilsci.pitt.edu/programs/visiting-fellows/program-overview/

The 2026 - 2027 Fellows will join *Senior Visiting Fellow, **Nick Huggett*
 - https://phil.uic.edu/profiles/huggett-nick/
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