Ian Quah

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Ian Quah

Interests: Neural Computation, Deep Reinforcement Learning, Biologically-inspired Algorithms


A subset of my research interests:

1) Neural Computation:

- Explore the computational capabilities of individual neurons and neural circuits.
- develop a coherent terminology for describing the assembly and integratian of neurons in constructing these circuits.

2) Deep Reinforcement Learning:

Leverage insights from psychology and neuroscience, with a specific emphasis on memory formation, memory consolidation, and learning, to enhance deep reinforcement learning.

3) Biologically-Inspired Algorithms:

Examine the biological underpinnings of learning and apply this knowledge to improve deep reinforcement learning and reinforcement learning algorithms.

See: "Bio-Inspired Hashing for Unsupervised Similarity Search" and "Neuronal Circuit Policies" and "Reinforcement Learning Fast and Slow"