Browsing Computer Science by Supervisor "Eliasmith, Chris"
Now showing items 1-7 of 7
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Biologically inspired methods in speech recognition and synthesis: closing the loop
(University of Waterloo, 2016-02-18)Current state-of-the-art approaches to computational speech recognition and synthesis are based on statistical analyses of extremely large data sets. It is currently unknown how these methods relate to the methods that ... -
Computational Mechanisms of Language Understanding and Use in the Brain and Behaviour
(University of Waterloo, 2020-10-15)Linguistic communication is a unique characteristic of intelligent behaviour that distinguishes humans from non-human animals. Natural language is a structured, complex communication system supported by a variety of ... -
Continuous Spatial and Temporal Representations in Machine Vision
(University of Waterloo, 2021-06-02)This thesis explores continuous spatial and temporal representations in machine vision. For spatial representations, we explore the Spatial Semantic Pointer as a biologically plausible representation of continuous space ... -
Dynamical Systems in Spiking Neuromorphic Hardware
(University of Waterloo, 2019-05-10)Dynamical systems are universal computers. They can perceive stimuli, remember, learn from feedback, plan sequences of actions, and coordinate complex behavioural responses. The Neural Engineering Framework (NEF) provides ... -
Harnessing Neural Dynamics as a Computational Resource
(University of Waterloo, 2022-01-10)Researchers study nervous systems at levels of scale spanning several orders of magnitude, both in terms of time and space. While some parts of the brain are well understood at specific levels of description, there are few ... -
Spaun 2.0: Extending the World’s Largest Functional Brain Model
(University of Waterloo, 2018-05-17)Building large-scale brain models is one method used by theoretical neuroscientists to understand the way the human brain functions. Researchers typically use either a bottom-up approach, which focuses on the detailed ... -
A spiking neural network of state transition probabilities in model-based reinforcement learning
(University of Waterloo, 2017-10-23)The development of the field of reinforcement learning was based on psychological studies of the instrumental conditioning of humans and other animals. Recently, reinforcement learning algorithms have been applied to ...