Search for tag: "science"

Taylor Sloop - Porosity Allows for Tuning of Dynamic Tensile Failure

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Vladimir Rosenhaus - Feynman rules for wave turbulence

It has long been known that weakly nonlinear field theories can have a late-time stationary state that is not the thermal state, but a wave turbulent state (the Kolmogorov-Zakharov state) with a…

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Ellen Zegura - Old and New Challenges in Networking, Including the Computing Kind

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Daniel Floryan - Charting dynamics from data

We often find ourselves working with systems for which governing equations are unknown, or if they are known, they may be high-dimensional to the point of being difficult to analyze and prohibitively…

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Carlos Pérez De Jesús - Data-driven estimation of inertial manifold dimension for chaotic Kolmogorov flow and time evolution on the manifold

Model reduction techniques have previously been applied to evolve the Navier-Stokes equations in time, however finding the minimal dimension needed to correctly capture the key dynamics is not a…

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Michael Graham, Kevin Zeng - Deep Reinforcement Learning Using Data-Driven Reduced-Order Models Discovers and Stabilizes Low Dissipation Equilibria

Part 2: Deep reinforcement learning (RL), a data-driven method capable of discovering complex control strategies for high-dimensional systems, requires substantial interactions with the target…

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Michael Graham, Alec Linot - Data-driven dimension reduction, dynamic modeling, and control of complex chaotic systems

PART 1Speaker Mike Graham Overview: Data-driven dimension reduction, dynamic modeling, and control of complex chaotic systemsOur overall aim is to combine ideas from dynamical systems theory and…

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Gideon Marcus - What Science Fiction Got Wrong...and Right! (and how you make the future)

In the 1950s and '60s, scientists and engineers were hailed as saints of progress. People believed that technology would solve all of the world's problems. But the science fiction and…

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Ruth Kanfer - Ageless Talent: Enhancing the Performance and Well-Being of Your Age-Diverse Workforce

Kanfer will discuss the book’s strategies and tools for addressing problems related to employee motivation, performance, and well-being in the context of rapid technological and social change.…

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Prevent Symposium - Closing Remarks

4:50 p.m Closing Discussion: Symposium Chairs 5:20 p.m. Closing Remarks: Elebeoba May, NSF

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Prevent Symposium - Session 4, Physiological and Environmental Level Theme

Session 4, Physiological and Environmental Level Theme Chairs: Krista Wigginton and John Yin2:10 p.m. Denise Kirschner, Michigan, Plenary Talk 2:30 p.m. Vipin Kumar, UMN , Presentation 2:40 p.m. Rita…

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Prevent Symposium - Session 3, Population Level Theme

Session 3, Population Level Theme Chairs: B. Aditya Prakash and Paul Torrens10:30 a.m. Bryan Grenfell, Princeton, Plenary Talk 10:50 a.m. Bin Yu, UC Berkeley, Presentation 11:00 a.m. Jordan Peccia,…

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Prevent Symposium - Session 2, Molecular Level Theme

Session 2, Molecular Level Theme Chairs: John Yin and Paul Torrens2:25 p.m. Paul Turner, Yale, Plenary Talk 2:45 p.m. Marc Riedel, UMN, Presentation 2:55 p.m. David Van Valen, Caltech, Presentation…

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Prevent Symposium - Session 1, End-to-End Theme

Session 1, End-to-End Theme Chairs: B. Aditya Prakash and Krista Wigginton10:45 a.m. Madhav Marathe, UVA, Plenary Talk 11:05 a.m. Debra Peters, USDA, Presentation 11:15 a.m. Ruian Ke, LANL,…

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Prevent Symposium - Opening and Welcome Remarks, Technical Backgrounds

10:00 a.m. Opening Remarks: Sethuraman Panchanathan, NSF Director 10:10 a.m Welcome Statement: Mitra Basu, NSF 10:15 a.m. Technical Background: Symposium Chairs

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Alexander Gray - Logical Neural Networks: Towards Unifying Statistical and Symbolic AI

Recently there has been renewed interest in the long-standing goal of somehow unifying the capabilities of both statistical AI (learning and prediction) and symbolic AI (knowledge representation and…

From  Katie Gentilello 44 plays 0