Dynamical Intelligence Group (DIG)

Research Group @ Johns Hopkins University Electrical and Computer Engineering Department

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DIG is an interdisciplinary group of researchers and students who are interested in understanding the dynamics of learning and the learning of dynamics in artificial and biological systems. We work in the intersection of dynamical systems and control theory, machine learning, and neuroscience.

news

Dec 19, 2015 New preprint out on grid cell computation: Distance by de-correlation: Computing distance with heterogeneous grid cells. A great collaboration with Priti Dasbehera and Akshunna S. Dogra!

selected publications

  1. Chaos
    Koopman learning with episodic memory
    William T. Redman, Dean Huang, Maria Fonoberova, and 1 more author
    Chaos: An Interdisciplinary Journal of Nonlinear Science, 2025
  2. NeurIPS
    Identifying equivalent training dynamics
    William T. Redman, Juan Bello-Rivas, Maria Fonoberova, and 3 more authors
    Advances in Neural Information Processing Systems, 2024
  3. NeurIPS
    Not so griddy: Internal representations of RNNs path integrating more than one agent
    William T. Redman, Francisco Acosta, Santiago Acosta-Mendoza, and 1 more author
    Advances in Neural Information Processing Systems, 2024