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Carnegie Mellon University Department of Philosophy @UC1KcOG1kfQXA7QU7G_ODjjg@youtube.com

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Carnegie Mellon University, Dietrich College of Humanities a


02:13:08
Cisinski, Nguyen, Walde: Univalent Directed Type theory, Part 3
02:10:22
Cisinski, Nguyen, Walde: Univalent Directed Type theory, Part 2
01:43:20
Cisinski, Nguyen, Walde: Univalent Directed Type theory, Part 1
01:34
Why study Logic & Computation?
02:21
The Logic & Computation Major at Carnegie Mellon University
01:18:47
Mike Shulman: Towards Third-Generation HOTT, Part 3
01:16:14
Mike Shulman: Towards Third-Generation HOTT, Part 2
01:23:32
Mike Shulman: Towards Third-Generation HOTT, Part 1
01:20:35
Nagel Lecture 2013 2
01:12:38
Nagel Lecture 2013 3
01:23:20
André Joyal "Three mutations of topos theory" Thursday, February 15, 2018
01:17:09
Nagel Lecture 2013 1
01:11:22
Dana Scott - What is explicit mathematics? Oct. 27, 2017
54:41
Causal Discovery from Mass Cytometry Data - Ioannis Tsamardinos
41:45
Biomolecular network models from single cell data - Karen Sachs
57:04
Causal Models from Online Course & Tutor Logs; and Searching for mediation models in ITS data
40:35
The worldwide leaf economic spectrum - Bill Shipley
44:52
Two applications of causal discovery in climate science - Imme Ebert-Uphoff
39:51
IMaGES in the Brain - Catherine Hanson
41:32
Strategies for Discovering Mechanisms of Mind using fMRI - Joe Ramsey
46:39
Causality workbench - Isabelle Guyon
41:02
All of causal discovery - Frederick Eberhardt
48:08
Causal model search applied to economics: gains, pitfalls and challenges - Alessio Moneta
40:19
The Causal Structure of the Vector Autoregression in Economics - Kevin Hoover
48:27
Learning gene regulatory networks - Marloes Maathius
40:11
Brain Connectivity Analysis: from Unimodal to Multimodal - Sergey Plis
46:45
Approaches to two problems in causal discovery searches on functional MRI data - Kathleen Gates
08:36
Unsolved Problems - Clark Glymour and Richard Scheines
53:05
On Micro Economics I: The Use of TETRAD for Demand Specification - David Bessler
02:02:34
Tutorial on Causal Learning - Richard Scheines