Interpretable Machine Learning in Natural and Social Sciences

Program

Summer Cluster: Interpretable Machine Learning

Location

Calvin Lab Auditorium

Date

Tuesday, June 28 – Thursday, June 30, 2022

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All talks are in PST Time. Schedule subject to change.

9 – 9:20 a.m.

Coffee and Check-In

9:20 – 9:30 a.m.

Opening Remarks

9:30 – 10 a.m.

Goals And Interpretable Variables In Neuroscience

David Danks (University of California, San Diego)

10 – 10:30 a.m.

Break

10:30 – 11 a.m.

Accuracy and Interpretability Through the Lens of Human-AI Teaming

Sina Fazelpour (Northeastern University)

11 a.m. – 12 p.m.

Panel on Societal Dimensions of Explanation

David Danks (University of California, San Diego),
Sina Fazelpour (Northeastern University)

12 – 3 p.m.

Lunch

3 – 3:30 p.m.

Conceptual Challenges In Connecting Interpretability And Causality

Alex D'Amour (Google Brain)

3:30 – 4 p.m.

Break

4 – 4:30 p.m.

Explanation: A(N Abridged) Survey

Joe Halpern (Cornell University)

4:30 – 5:30 p.m.

Panel on Causality

Alex D'Amour (Google Brain),
Joe Halpern (Cornell University)

5:30 – 6:30 p.m.

Reception

9 – 10 a.m.

Coffee and Check-In

10 – 10:30 a.m.

Interpretability In Atomic-Scale Machine Learning

Michele Ceriotti (Swiss Federal Institute of Technology in Lausanne)

10:30 – 11 a.m.

Break

11 – 11:30 a.m.

Interpreting Machine Learning From the Perspective of Nonequilibrium Systems

David Limmer (University of California, Berkeley)

11:30 a.m. – 12:30 p.m.

Panel on Interpretability in the Physical Sciences

Michele Ceriotti (Swiss Federal Institute of Technology in Lausanne),
David Limmer (University of California, Berkeley)

12:30 – 3 p.m.

Lunch

3 – 3:30 p.m.

Interpreting Deep Learning Models Of Functional Genomics Data To Decode Regulatory Sequence Syntax And Genetic Variation

Anshul Kundaje (Stanford University)

3:30 – 4 p.m.

Break

4 – 4:30 p.m.

Machine Learning, Deep Networks and Interpretability in Systems, Cognitive and Computational Neuroscience

Jack Gallant (University of California, Berkeley)

4:30 – 5:30 p.m.

Panel on Interpretability in the Biological Sciences

Anshul Kundaje (Stanford University),
Jack Gallant (University of California, Berkeley)

9 – 9:30 a.m.

Coffee and Check-In

9:30 – 10 a.m.

Interpretability and Algorithmic Fairness

Alice Xiang (Sony AI)

10 – 10:30 a.m.

Break

10:30 – 11 a.m.

Legal Barriers To Interpretable Machine Learning

Rebecca Wexler (Berkeley Center for Law & Technology)

11 – 11:30 a.m.

Platform-supported Auditing Of Social Media Algorithms For Public Interest

Aleksandra Korolova (University of Southern California)

11:30 a.m. – 12:30 p.m.

Panel on Interpretability in the Law

Alice Xiang (Sony AI),
Aleksandra Korolova (University of Southern California),
Rebecca Wexler (Berkeley Center for Law & Technology)

12:30 – 2 p.m.

Group Lunch (boxed lunches provided)

2 – 4:30 p.m.

Group hike