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Gregoire Montavon - Towards Higher-Order and Disentangled Explainable AI - IPAM at UCLA
Presenter
- Gregoire Montavon
January 11, 2023
IPAM
Osbert Bastani - Interpretable Machine Learning via Program Synthesis - IPAM at UCLA
Presenter
- Osbert Bastani
January 10, 2023
IPAM
Wojciech Samek - Concept-Level Explainable AI - IPAM at UCLA
Presenter
- Wojciech Samek
January 10, 2023
IPAM
Frederick Klauschen - AI in cancer research and diagnostics - IPAM at UCLA
Presenter
- Frederick Klauschen
January 10, 2023
IPAM
Klaus Robert Muller - AI for the Sciences: Recent Developments for XAI - IPAM at UCLA
Presenter
- Klaus Muller
January 9, 2023
IPAM
Bolei Zhou - From Network Dissection to Policy Dissection: Emergent Concepts in Deep Representations
Presenter
- Bolei Zhou
January 9, 2023
IPAM
Xiao Fu - Multiview and Self-Supervised Representation Learning: Nonlinear Mixture Identification
Presenter
- Xiao Fu
January 9, 2023
IPAM
Jaesik Choi - Explainable AI to Analyze Internal Decision Mechanism of Deep Neural Networks
Presenter
- Jaesik Choi
January 9, 2023
IPAM
Bin Yu - Interpreting Deep Neural Networks towards Trustworthiness - IPAM at UCLA
Presenter
- Bin Yu
January 9, 2023
IPAM
Explainable AI (XAI) for Climate Science: Detection, Prediction and Discovery
Presenter
- Elizabeth Barnes
October 31, 2022
IMSI
Oliver Eberle - Interpretability for Deep Learning: Theory, Applications and Scientific Insights
Presenter
- Oliver Eberle
October 17, 2024
IPAM
Dealing with COVID-19 in Theory and Practice: Session II: Data Science I
Presenters
- Mihaela van der Schaar
- Michael Jordan
October 29, 2020
IMSI