no code implementations • 6 Jul 2021 • Dumindu Tissera, Rukshan Wijessinghe, Kasun Vithanage, Alex Xavier, Subha Fernando, Ranga Rodrigo
Having multiple parallel convolutional/dense operations in each layer solves this problem, but without any context-dependent allocation of resources among these operations: the parallel computations tend to learn similar features making the widening process less effective.
no code implementations • 6 Jul 2021 • Dumindu Tissera, Kasun Vithanage, Rukshan Wijesinghe, Alex Xavier, Sanath Jayasena, Subha Fernando, Ranga Rodrigo
The network parameters pose as the parameters of those distributions.
no code implementations • 16 Feb 2021 • Rukshan Wijesinghe, Kasun Vithanage, Dumindu Tissera, Alex Xavier, Subha Fernando, Jayathu Samarawickrama
Recent advances in Reinforcement Learning (RL) have surpassed human-level performance in many simulated environments.
no code implementations • 24 Jun 2020 • Dumindu Tissera, Kasun Vithanage, Rukshan Wijesinghe, Kumara Kahatapitiya, Subha Fernando, Ranga Rodrigo
As opposed to conventional network widening, multi-path architectures restrict the quadratic increment of complexity to a linear scale.