Please, take into account that this program is still subject to changes and updates.
Because of this, we kindly ask you to check this website regularly.
Thursday, 20th October
9:15 – 09:30
9:30 – 10:20
10:30 – 11:20
11:30 – 12:20
12:20 – 13:30
13:30 – 14:20
14:30 – 15:20
15:20 –16:00
16:00 –16:50
17:00 – 17:50
Welcome
Ben Jantzen (Virginia Tech): Machines and Ontological Induction
Kate Vredenburgh (LSE): Against Decision Thresholds
Donal Khosrowi (Hannover): Generalization in Machine Learning: A Plea for Better Theory
Lunch Break
Tim Räz (Bern): Machine Learning and the Quest for Objectivity in Climate Model Parameterization
Winnie Ma (KCL): Profiling Patients
Coffee Break/Snacks
Heather Champion (Rotman Institute): A Transferrable Conceptual Toolbox for Characterizing Novelty with Machine-led Exploratory Experiments
Cameron Buckner (Houston): On Measures Relating Representations in DNNs to Representations in the Brain
Dinner at Caro’s
Friday, 21st October
9:00 – 09:30
9:30 – 10:20
10:30 – 11:20
11:30 – 12:20
12:20 – 13:30
13:30 – 14:20
14:30 – 15:20
15:20 –16:00
16:00 –16:50
17:00 – 17:50
Coffee
Uljana Feest (Hannover): Big Data and Machine Learning in the Measurement of Personality Traits
David Watson (KCL): Probing Errors with Explainable Artificial Intelligence (joint work with D. Mayo)
Hong Yu Wong (Tübingen): Varieties of Intelligence?
Lunch Break
Jan-Willem Romeijn (Groningen): Machine Learning, or: The Return of Instrumentalism
Brandon James Ashby (York): Machine Learning Models of High-Level Vision: On the Format and Character of Category Perception
Coffee Break/Snacks
Lily Hu (Yale): TBA
Zachary Lipton (CMU): Induction, Identification, Interpolation, and Extrapolation in Machine Learning
Dinner at Freistil
Saturday, 22nd October
10:00 – 10:30
10:30 – 11:20
11:30 – 12:20
12:20 – 13:30
13:30 – 14:20
14:30 – 15:20
15:20 –16:00
Coffee
Emily Sullivan (Eindhoven): Idealization in Machine Learning and XAI
Bojana Grujicic (UCL): Deep Neural Networks as Mechanistic Explanations of Object Recognition: In Search of the Explanans (CANCELLED)
Rabanus Derr (Tübingen): Fairness and Randomness in Machine Learning: Statistical Independence and Relativization
Lunch Break
Frederick Eberhardt (Caltech): Continuous Causal Macro Variables
Katie Creel (Northeastern): A Molineux Problem for Automated Science
Tom Sterkenburg (LMU): Machine Learning and the Philosophical Problem of Induction
Closing Words and Drinks