Search Results for author: Sreenatha Anavatti

Found 4 papers, 2 papers with code

Scalable Adversarial Online Continual Learning

1 code implementation4 Sep 2022 Tanmoy Dam, Mahardhika Pratama, Md Meftahul Ferdaus, Sreenatha Anavatti, Hussein Abbas

Adversarial continual learning is effective for continual learning problems because of the presence of feature alignment process generating task-invariant features having low susceptibility to the catastrophic forgetting problem.

Continual Learning Meta-Learning

Towards Crossing the Reality Gap with Evolved Plastic Neurocontrollers

no code implementations23 Feb 2020 Huanneng Qiu, Matthew Garratt, David Howard, Sreenatha Anavatti

A critical issue in evolutionary robotics is the transfer of controllers learned in simulation to reality.

Evolving Spiking Neural Networks for Nonlinear Control Problems

no code implementations4 Mar 2019 Huanneng Qiu, Matthew Garratt, David Howard, Sreenatha Anavatti

Spiking Neural Networks are powerful computational modelling tools that have attracted much interest because of the bioinspired modelling of synaptic interactions between neurons.

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