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05/18/2022
Policy Distillation with Selective Input Gradient Regularization for Efficient Interpretability
Although deep Reinforcement Learning (RL) has proven successful in a wid...
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05/22/2021
Edelman's Steps Toward a Conscious Artifact
In 2006, during a meeting of a working group of scientists in La Jolla, ...
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05/05/2021
Dynamic Reliability Management in Neuromorphic Computing
Neuromorphic computing systems uses non-volatile memory (NVM) to impleme...
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02/25/2021
Neuroevolution of a Recurrent Neural Network for Spatial and Working Memory in a Simulated Robotic Environment
Animals ranging from rats to humans can demonstrate cognitive map capabi...
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02/10/2021
Domain Adaptation In Reinforcement Learning Via Latent Unified State Representation
Despite the recent success of deep reinforcement learning (RL), domain a...
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03/21/2020
PyCARL: A PyNN Interface for Hardware-Software Co-Simulation of Spiking Neural Network
We present PyCARL, a PyNN-based common Python programming interface for ...
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09/21/2019
Deep Reinforcement Learning with Modulated Hebbian plus Q Network Architecture
This paper introduces the modulated Hebbian plus Q network architecture ...
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09/14/2019
Neuromodulated Patience for Robot and Self-Driving Vehicle Navigation
Robots and self-driving vehicles face a number of challenges when naviga...
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09/04/2019
Mapping Spiking Neural Networks to Neuromorphic Hardware
Neuromorphic hardware platforms implement biological neurons and synapse...
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03/09/2019
Sparse Representations for Object and Ego-motion Estimation in Dynamic Scenes
Dynamic scenes that contain both object motion and egomotion are a chall...
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02/16/2019
Neuromodulated Goal-Driven Perception in Uncertain Domains
In uncertain domains, the goals are often unknown and need to be predict...
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12/04/2018
Making BREAD: Biomimetic strategies for Artificial Intelligence Now and in the Future
The Artificial Intelligence (AI) revolution foretold of during the 1960s...
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07/18/2017
