research
∙
11/01/2018
Liquid Time-constant Recurrent Neural Networks as Universal Approximators
In this paper, we introduce the notion of liquid time-constant (LTC) rec...
share
research
∙
09/11/2018
Re-purposing Compact Neuronal Circuit Policies to Govern Reinforcement Learning Tasks
We propose an effective method for creating interpretable control agents...
research
∙
09/11/2018
Response Characterization for Auditing Cell Dynamics in Long Short-term Memory Networks
In this paper, we introduce a novel method to interpret recurrent neural...
research
∙
03/22/2018
Neuronal Circuit Policies
We propose an effective way to create interpretable control agents, by r...
research
∙
11/09/2017
Worm-level Control through Search-based Reinforcement Learning
Through natural evolution, nervous systems of organisms formed near-opti...
research
∙
11/04/2017
Searching for Biophysically Realistic Parameters for Dynamic Neuron Models by Genetic Algorithms from Calcium Imaging Recording
Individual Neurons in the nervous systems exploit various dynamics. To c...
research
∙
03/18/2017
An Automated Auto-encoder Correlation-based Health-Monitoring and Prognostic Method for Machine Bearings
This paper studies an intelligent ultimate technique for health-monitori...
research
∙
03/18/2017
SIM-CE: An Advanced Simulink Platform for Studying the Brain of Caenorhabditis elegans
We introduce SIM-CE, an advanced, user-friendly modeling and simulation ...
research
∙
03/18/2017
Non-Associative Learning Representation in the Nervous System of the Nematode Caenorhabditis elegans
Caenorhabditis elegans (C. elegans) illustrated remarkable behavioral pl...
research
∙
02/24/2017
