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Aishni Parab - Extracting Structured Data from Multi-Modal Input - IPAM at UCLA
Presenter
- Aishni Parab
November 7, 2024
IPAM
Sean Tull - Towards Compositional Interpretability for XAI - IPAM at UCLA
Presenter
- Sean Tull
November 6, 2024
IPAM
David Spivak - Plausible Fiction: Accounting for Actualizing Potential - IPAM at UCLA
Presenter
- David Spivak
November 5, 2024
IPAM
Mehrnoosh Sadrzadeh - How can large language models learn from humans? - IPAM at UCLA
Presenter
- Mehrnoosh Sadrzadeh
November 5, 2024
IPAM
Sanjoy Dasgupta - Neural machines: From fruit flies to embedded devices - IPAM at UCLA
Presenter
- Sanjoy Dasgupta
November 4, 2024
IPAM
Levi Lelis - Learning Libraries of Programmatic Policies - IPAM at UCLA
Presenter
- Levi Lelis
November 4, 2024
IPAM
Adityanarayanan Radhakrishnan - How do neural networks learn features from data? - IPAM at UCLA
Presenter
- Adityanarayanan Radhakrishnan
October 18, 2024
IPAM
Leena Vankadara - Scaling Insights from Infinite-Width Theory for Next Gen Architecture & Learning
Presenter
- Leena Vankadara
October 18, 2024
IPAM
Dmitry Krotov - Generative AI models through the lens of Dense Associative Memory - IPAM at UCLA
Presenter
- Dmitry Krotov
October 17, 2024
IPAM
Oliver Eberle - Interpretability for Deep Learning: Theory, Applications and Scientific Insights
Presenter
- Oliver Eberle
October 17, 2024
IPAM