Chris Eliasmith

Chris Eliasmith

University of Waterloo

H-index: 49

North America-Canada

About Chris Eliasmith

Chris Eliasmith, With an exceptional h-index of 49 and a recent h-index of 33 (since 2020), a distinguished researcher at University of Waterloo, specializes in the field of theoretical neuroscience, brain modelling, machine learning, artificial intelligence, philosophy of mind.

His recent articles reflect a diverse array of research interests and contributions to the field:

A scalable spiking amygdala model that explains fear conditioning, extinction, renewal and generalization

Improving reinforcement learning with biologically motivated continuous state representations

Modelling neural probabilistic computation using vector symbolic architectures

Bridging Cognitive Architectures and Generative Models with Vector Symbolic Algebras

Exploiting semantic information in a spiking neural SLAM system

A Unified Neurocomputational Model of Prospective and Retrospective Timing

Neuromorphic control of a simulated 7-DOF arm using Loihi

Biologically-Based Computation: How Neural Details and Dynamics Are Suited for Implementing a Variety of Algorithms

Chris Eliasmith Information

University

Position

Professor

Citations(all)

11301

Citations(since 2020)

5371

Cited By

8889

hIndex(all)

49

hIndex(since 2020)

33

i10Index(all)

135

i10Index(since 2020)

91

Email

University Profile Page

University of Waterloo

Google Scholar

View Google Scholar Profile

Chris Eliasmith Skills & Research Interests

theoretical neuroscience

brain modelling

machine learning

artificial intelligence

philosophy of mind

Top articles of Chris Eliasmith

Title

Journal

Author(s)

Publication Date

A scalable spiking amygdala model that explains fear conditioning, extinction, renewal and generalization

European Journal of Neuroscience

Peter Duggins

Chris Eliasmith

2024/4/14

Improving reinforcement learning with biologically motivated continuous state representations

Proceedings of the 21st International Conference on Cognitive Modeling

Madeleine Bartlett

Kathryn Simone

ND Dumont

M Furlong

Chris Eliasmith

...

2023

Modelling neural probabilistic computation using vector symbolic architectures

Cognitive Neurodynamics

P Michael Furlong

Chris Eliasmith

2023/12/16

Bridging Cognitive Architectures and Generative Models with Vector Symbolic Algebras

Proceedings of the AAAI Symposium Series

P Michael Furlong

Chris Eliasmith

2023

Exploiting semantic information in a spiking neural SLAM system

Frontiers in Neuroscience

Nicole Sandra-Yaffa Dumont

P Michael Furlong

Jeff Orchard

Chris Eliasmith

2023/7/5

A Unified Neurocomputational Model of Prospective and Retrospective Timing

Joost de Jong

Aaron R Voelker

Terrence C Stewart

Elkan Akyurek

Chris Eliasmith

...

2023/6/21

Neuromorphic control of a simulated 7-DOF arm using Loihi

Neuromorphic Computing and Engineering

Travis DeWolf

Kinjal Patel

Pawel Jaworski

Roxana Leontie

Joe Hays

...

2023/2/6

Biologically-Based Computation: How Neural Details and Dynamics Are Suited for Implementing a Variety of Algorithms

Brain Sciences

Nicole Sandra-Yaffa Dumont

Andreas Stöckel

P Michael Furlong

Madeleine Bartlett

Chris Eliasmith

...

2023/1/31

A model of path integration that connects neural and symbolic representation

Proceedings of the Annual Meeting of the Cognitive Science Society

Nicole Sandra-Yaffa Dumont

Jeff Orchard

Chris Eliasmith

2022

Computational properties of multi-compartment LIF neurons with passive dendrites

Neuromorphic Computing and Engineering

Andreas Stöckel

Chris Eliasmith

2022/6/15

Fractional binding in vector symbolic architectures as quasi-probability statements

Proceedings of the annual meeting of the cognitive science society

Michael Furlong

Chris Eliasmith

2022

Fractional binding in vector symbolic representations for efficient mutual information exploration

Proceedings of the ICRA Workshop: Towards Curious Robots: Modern Approaches for Intrinsically-Motivated Intelligent Behavior

P Michael Furlong

Terrence C Stewart

Chris Eliasmith

2022/6

Continuous then discrete: A recommendation for building robotic brains

Chris Eliasmith

P Michael Furlong

2022/1/11

BatSLAM: Neuromorphic spatial reasoning in 3D environments

Brent Komer

Pawel Jaworski

Steven Harbour

Chris Eliasmith

Travis DeWolf

2022/9/18

Reinforcement Learning, Social Value Orientation, and Decision Making: Computational

Proceedings of the Annual Meeting of the Cognitive Science Society

Peter Duggins

Terrence C Stewart

Chris Eliasmith

2022

Constructing functional models from biophysically-detailed neurons

PLoS Computational Biology

Peter Duggins

Chris Eliasmith

2022/9/8

Learned legendre predictor: Learning with compressed representaitons for efficient online multistep prediction

P Michael Furlong

Andreas Stöckel

Terry Stewart

Chris Eliasmith

2022

Debugging using orthogonal gradient descent

arXiv preprint arXiv:2206.08489

Narsimha Chilkuri

Chris Eliasmith

2022/6/17

Modèle neuronal unifié du traitement conscient et inconscient

Hugo Chateau-Laurent

Frédéric Alexandre

Chris Eliasmith

Serge Thill

2021/3/13

Simulating and predicting dynamical systems with spatial semantic pointers

Neural Computation

Aaron R Voelker

Peter Blouw

Xuan Choo

Nicole Sandra-Yaffa Dumont

Terrence C Stewart

...

2021/7/26

See List of Professors in Chris Eliasmith University(University of Waterloo)

Co-Authors

H-index: 76
Paul Thagard

Paul Thagard

University of Waterloo

H-index: 60
Steve Furber

Steve Furber

Manchester University

H-index: 48
Kwabena Boahen

Kwabena Boahen

Stanford University

H-index: 34
Jorg Conradt

Jorg Conradt

Kungliga Tekniska högskolan

H-index: 33
Terrence C Stewart

Terrence C Stewart

University of Waterloo

H-index: 32
Mark Laubach

Mark Laubach

American University

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