no code implementations • 21 Jun 2018 • Andrew D. King, William Bernoudy, James King, Andrew J. Berkley, Trevor Lanting
The coherent Ising machine is an optical processor that uses coherent laser pulses, but does not employ coherent quantum dynamics in a computational role.
Quantum Physics Emerging Technologies
no code implementations • 19 Feb 2019 • Tellen Bennett, Seth Russell, James King, Lisa Schilling, Chan Voong, Nancy Rogers, Bonnie Adrian, Nicholas Bruce, Debashis Ghosh
Interest in an electronic health record-based computational model that can accurately predict a patient's risk of sepsis at a given point in time has grown rapidly in the last several years.
1 code implementation • 6 May 2019 • Pramod Kumbhar, Omar Awile, Liam Keegan, Jorge Blanco Alonso, James King, Michael Hines, Felix Schürmann
Here, we describe a new code generation framework (NMODL) for an existing DSL in the NEURON framework, a widely used software for massively parallel simulation of biophysically detailed brain tissue models.
Mathematical Software Neurons and Cognition
no code implementations • 24 Jun 2019 • James King, Masoud Mohseni, William Bernoudy, Alexandre Fréchette, Hossein Sadeghi, Sergei V. Isakov, Hartmut Neven, Mohammad H. Amin
Reverse annealing enables the development of genetic algorithms that use quantum fluctuation for mutations and classical mechanisms for the crossovers -- we refer to these as Quantum-Assisted Genetic Algorithms (QAGAs).
no code implementations • 30 Sep 2021 • James King, Ramon Viñas Torné, Alexander Campbell, Pietro Liò
Our paper compares the pre-upsampling AudioUNet to a new generative model that upsamples the signal before using deep learning to transform it into a more believable signal.
1 code implementation • 15 Jul 2022 • Yang Xiao, Xubo Liu, James King, Arshdeep Singh, Eng Siong Chng, Mark D. Plumbley, Wenwu Wang
Experimental results on the DCASE 2019 Task 1 and ESC-50 dataset show that our proposed method outperforms baseline continual learning methods on classification accuracy and computational efficiency, indicating our method can efficiently and incrementally learn new classes without the catastrophic forgetting problem for on-device environmental sound classification.