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Chris Eliasmith

Chris Eliasmith

D-Index & Metrics

Computer Science

D-Index
44
Citations
10757
World Ranking
7443
National Ranking
298

Overview

Chris Eliasmith is affiliated with the University of Waterloo in Canada. Their research primarily spans the fields of Computer Science, Engineering, and Neuroscience, reflecting a multidisciplinary approach to computational and cognitive studies.

The scientist's work covers several prominent areas including Advanced Memory and Neural Computing, Neural dynamics and brain function, Ferroelectric and Negative Capacitance Devices, as well as Neural Networks and Reservoir Computing. Additional interests include Neural Networks and Applications, Topic Modeling, and Memory and Neural Mechanisms.

Recent scholarly output features publications in various recognized venues such as arXiv (Cornell University), Psychological Review, Neuromorphic Computing and Engineering, Neural Computation, and Brain Sciences.

  • Comparing Loihi with a SpiNNaker 2 prototype on low-latency keyword spotting and adaptive robotic control (2021, Neuromorphic Computing and Engineering)
  • Simulating and Predicting Dynamical Systems With Spatial Semantic Pointers (2021, Neural Computation)
  • A Spiking Neural Network for Image Segmentation (2021, arXiv [Cornell University])
  • Biologically-Based Computation: How Neural Details and Dynamics Are Suited for Implementing a Variety of Algorithms (2023, Brain Sciences)
  • A unified neurocomputational model of prospective and retrospective timing (2025, Psychological Review)

Chris Eliasmith collaborates frequently with a core group of researchers, including Aaron R. Voelker, Terrence C. Stewart, P. Michael Furlong, Nicole Sandra-Yaffa Dumont, and Xuan Choo. These partnerships contribute to a range of topics connected to neural computation and cognitive modeling.

Publication venues with multiple papers include arXiv (Cornell University) with eight contributions, Psychological Review and Neuromorphic Computing and Engineering with three publications each, Neural Computation, and Brain Sciences.

  • arXiv (Cornell University)
  • Psychological Review
  • Neuromorphic Computing and Engineering
  • Neural Computation
  • Brain Sciences

  • Aaron R. Voelker
  • Terrence C. Stewart
  • P. Michael Furlong
  • Nicole Sandra-Yaffa Dumont
  • Xuan Choo

  • Computer Science
  • Engineering
  • Neuroscience

  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Cognitive Neuroscience
  • Aerospace Engineering
  • Computer Vision and Pattern Recognition

  • Advanced Memory and Neural Computing
  • Neural dynamics and brain function
  • Ferroelectric and Negative Capacitance Devices
  • Neural Networks and Reservoir Computing
  • Neural Networks and Applications
  • Topic Modeling
  • Memory and Neural Mechanisms

Best Publications

  • A Large-Scale Model of the Functioning Brain

    Chris Eliasmith;Terrence C. Stewart;Xuan Choo;Trevor Bekolay

  • Hyperopt: a Python library for model selection and hyperparameter optimization

    James Bergstra;Brent Komer;Chris Eliasmith;Dan Yamins

  • Neural engineering : computation, representation, and dynamics in neurobiological systems

    Chris Eliasmith;C. H. Anderson

  • How to Build a Brain: A Neural Architecture for Biological Cognition

    Chris Eliasmith

  • Nengo: a Python tool for building large-scale functional brain models.

    Trevor Bekolay;James Bergstra;Eric Hunsberger;Travis DeWolf

  • Hyperopt-Sklearn: Automatic Hyperparameter Configuration for Scikit-Learn

    Brent Komer;James Bergstra;Chris Eliasmith

  • Spiking Deep Networks with LIF Neurons

    Eric Hunsberger;Chris Eliasmith

  • Integrating structure and meaning: a distributed model of analogical mapping

    Chris Eliasmith;Paul Thagard

  • Braindrop: A Mixed-Signal Neuromorphic Architecture With a Dynamical Systems-Based Programming Model

    Alexander Neckar;Sam Fok;Ben V. Benjamin;Terrence C. Stewart

  • A Unified Approach to Building and Controlling Spiking Attractor Networks

    Chris Eliasmith

  • The third contender: A critical examination of the Dynamicist theory of cognition

    Chris Eliasmith

  • Concepts as Semantic Pointers: A Framework and Computational Model

    Peter Blouw;Eugene Solodkin;Paul Thagard;Chris Eliasmith

  • Benchmarking Keyword Spotting Efficiency on Neuromorphic Hardware

    Peter Blouw;Xuan Choo;Eric Hunsberger;Chris Eliasmith

  • A controlled attractor network model of path integration in the rat.

    John Conklin;Chris Eliasmith

  • The use and abuse of large-scale brain models.

    Chris Eliasmith;Oliver Trujillo

  • Deep networks for robust visual recognition

    Yichuan Tang;Chris Eliasmith

  • Fine-tuning and the stability of recurrent neural networks.

    David MacNeil;Chris Eliasmith

  • Training Spiking Deep Networks for Neuromorphic Hardware

    Eric Hunsberger;Chris Eliasmith

  • A Neural Model of Rule Generation in Inductive Reasoning

    Daniel Rasmussen;Chris Eliasmith

  • Learning to Select Actions with Spiking Neurons in the Basal Ganglia

    Terrence C. Stewart;Trevor Bekolay;Chris Eliasmith

  • Is the Brain a Quantum Computer

    Abninder Litt;Chris Eliasmith;Frederick W. Kroon;Steven Weinstein

  • Legendre Memory Units: Continuous-Time Representation in Recurrent Neural Networks

    Aaron R Voelker;Ivana Kajić;Chris Eliasmith

  • The third contender: a critical examination of the dynamicist theory of

    Chris Eliasmith

Frequent Co-Authors

Paul Thagard
Paul Thagard University of Waterloo
Steve Furber
Steve Furber University of Manchester
Kwabena Boahen
Kwabena Boahen Stanford University
William Bechtel
William Bechtel University of California, San Diego
Ralph Etienne-Cummings
Ralph Etienne-Cummings Johns Hopkins University
Giacomo Indiveri
Giacomo Indiveri University of Zurich
James Danckert
James Danckert University of Waterloo
Bradley C. Love
Bradley C. Love University College London
Hedderik van Rijn
Hedderik van Rijn University of Groningen

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