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Sylvia Biscoveanu of the Massachusetts Institute of Technology presents "Source characterization ... Katerina Chatziioannou of the California Institute of Technology presents "Introduction to Single ...

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Elaine Raybourn of Sandia National Laboratories presents "Sociotechnical aspects of new code ... use economic indicators like fuel price things like that and we're trying to pass this into a

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  • Sylvia Biscoveanu of the Massachusetts Institute of Technology presents "Source characterization ...
  • Katerina Chatziioannou of the California Institute of Technology presents "Introduction to Single ...
  • Elaine Raybourn of Sandia National Laboratories presents "Sociotechnical aspects of new code ...

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Image Reference Set

Lillian Ratliff - Learning via Conjectural Variations - IPAM at UCLA
Lillian Ratliff: Beyond Open Loop Thinking: A Prelude to Learning-Based Intelligent Systems
Lillian Ratliff
Sylvia Biscoveanu - Source characterization of individual compact binary coalescences - IPAM at UCLA
Katerina Chatziioannou - Introduction to Single Source Inference - IPAM at UCLA
Elaine Raybourn - Sociotechnical aspects of new code collaborations - IPAM at UCLA
Physics Panel - Accelerating Math and Theoretical Physics with AI - IPAM at UCLA
Spring 2024 Program "Geometry, Statistical Mechanics, and Integrability" IPAM at UCLA
Gradient Descent-Ascent Provably Converges to Strict Local Minmax Equilibria with a Finite Timescale
Beyond Open Loop Algorithm Design: Learning from Decision-Dependent Data
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Lillian Ratliff - Learning via Conjectural Variations - IPAM at UCLA

Lillian Ratliff - Learning via Conjectural Variations - IPAM at UCLA

Read more details and related context about Lillian Ratliff - Learning via Conjectural Variations - IPAM at UCLA.

Lillian Ratliff: Beyond Open Loop Thinking: A Prelude to Learning-Based Intelligent Systems

Lillian Ratliff: Beyond Open Loop Thinking: A Prelude to Learning-Based Intelligent Systems

Read more details and related context about Lillian Ratliff: Beyond Open Loop Thinking: A Prelude to Learning-Based Intelligent Systems.

Lillian Ratliff

Lillian Ratliff

... use economic indicators like fuel price things like that and we're trying to pass this into a

Sylvia Biscoveanu - Source characterization of individual compact binary coalescences - IPAM at UCLA

Sylvia Biscoveanu - Source characterization of individual compact binary coalescences - IPAM at UCLA

Recorded 20 September 2021. Sylvia Biscoveanu of the Massachusetts Institute of Technology presents "Source characterization ...

Katerina Chatziioannou - Introduction to Single Source Inference - IPAM at UCLA

Katerina Chatziioannou - Introduction to Single Source Inference - IPAM at UCLA

Recorded 15 November 2021. Katerina Chatziioannou of the California Institute of Technology presents "Introduction to Single ...

Elaine Raybourn - Sociotechnical aspects of new code collaborations - IPAM at UCLA

Elaine Raybourn - Sociotechnical aspects of new code collaborations - IPAM at UCLA

Recorded 15 March 2023. Elaine Raybourn of Sandia National Laboratories presents "Sociotechnical aspects of new code ...

Physics Panel - Accelerating Math and Theoretical Physics with AI - IPAM at UCLA

Physics Panel - Accelerating Math and Theoretical Physics with AI - IPAM at UCLA

Recorded 04 March 2026. Physics Panel Discussion: Zvi Bern of

Spring 2024 Program "Geometry, Statistical Mechanics, and Integrability" IPAM at UCLA

Spring 2024 Program "Geometry, Statistical Mechanics, and Integrability" IPAM at UCLA

Read more details and related context about Spring 2024 Program "Geometry, Statistical Mechanics, and Integrability" IPAM at UCLA.

Gradient Descent-Ascent Provably Converges to Strict Local Minmax Equilibria with a Finite Timescale

Gradient Descent-Ascent Provably Converges to Strict Local Minmax Equilibria with a Finite Timescale

Read more details and related context about Gradient Descent-Ascent Provably Converges to Strict Local Minmax Equilibria with a Finite Timescale.

Beyond Open Loop Algorithm Design: Learning from Decision-Dependent Data

Beyond Open Loop Algorithm Design: Learning from Decision-Dependent Data

Read more details and related context about Beyond Open Loop Algorithm Design: Learning from Decision-Dependent Data.