Search Results for author: Keichi Takahashi

Found 3 papers, 2 papers with code

Experimentally testable whole brain manifolds that recapitulate behavior

no code implementations • 20 Jun 2021 • Gerald M Pao, Cameron Smith, Joseph Park, Keichi Takahashi, Wassapon Watanakeesuntorn, Hiroaki Natsukawa, Sreekanth H Chalasani, Tom Lorimer, Ryousei Takano, Nuttida Rungratsameetaweemana, George Sugihara

Thus, as a final validation of how well GMN captures essential dynamic information, we show that the artificially generated time series can be used as a training set to predict out-of-sample observed fly locomotion, as well as brain activity in out of sample withheld data not used in model building.

Causal Inference Time Series +1

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Massively Parallel Causal Inference of Whole Brain Dynamics at Single Neuron Resolution

1 code implementation • 2 Dec 2020 • Wassapon Watanakeesuntorn, Keichi Takahashi, Kohei Ichikawa, Joseph Park, George Sugihara, Ryousei Takano, Jason Haga, Gerald M. Pao

Empirical Dynamic Modeling (EDM) is a nonlinear time series causal inference framework.

Causal Inference Time Series +1

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ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management

1 code implementation • SoftwareX 2020 • William F. Godoy, Norbert Podhorszki, Ruonan Wang, Chuck Atkins, Greg Eisenhauer, Junmin Gu, Philip Davis, Jong Choi, Kai Germaschewski, Kevin Huck, Axel Huebl, Mark Kim, James Kress, Tahsin Kurc, Qing Liu, Jeremy Logan, Kshitij Mehta, George Ostrouchov, Manish Parashar, Franz Poeschel, David Pugmire, Eric Suchyta, Keichi Takahashi, Nick Thompson, Seiji Tsutsumi, Lipeng Wan, Matthew Wolf, Kesheng Wu, Scott Klasky

We present ADIOS 2, the latest version of the Adaptable Input Output (I/O) System.

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