7 citations · 10 across the 13 of their papers we have counts for
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Quantum-Cognitive Neural Networks: Assessing Confidence and Uncertainty with Human Decision-Making Simulations
Milan Maksimovic, Ivan S. Maksymov
Modern machine learning (ML) systems excel in recognising and classifying images with remarkable accuracy. However, like many computer software systems, they can fail by generating…
Quantum-tunnelling deep neural network for optical illusion recognition
Ivan S. Maksymov
The discovery of the quantum tunnelling (QT) effect -- the transmission of particles through a high potential barrier -- was one of the most impressive achievements of quantum mech…
Classical and Quantum Physical Reservoir Computing for Onboard Artificial Intelligence Systems: A Perspective
A. H. Abbas, Hend Abdel-Ghani, Ivan S. Maksymov
Artificial intelligence (AI) systems of autonomous systems such as drones, robots and self-driving cars may consume up to 50% of total power available onboard, thereby limiting the…
Quantum Mechanics of Human Perception, Behaviour and Decision-Making: A Do-It-Yourself Model Kit for Modelling Optical Illusions and Opinion Formation in Social Networks
Ivan S. Maksymov
On the surface, behavioural science and physics seem to be two disparate fields of research. However, a closer examination of problems solved by them reveals that they are uniquely…
Reservoir Computing Using Measurement-Controlled Quantum Dynamics
A. H. Abbas, Ivan S. Maksymov
Physical reservoir computing (RC) is a machine learning algorithm that employs the dynamics of a physical system to forecast highly nonlinear and chaotic phenomena. In this paper,…
Magnetism-Inspired Quantum-Mechanical Model of Gender Fluidity
Ivan S. Maksymov
Quantum-mechanical models of human cognition, opinion formation and decision-making have changed the way we understand and predict human behaviour in many practical situations, inc…
Physical Reservoir Computing Enabled by Solitary Waves and Biologically-Inspired Nonlinear Transformation of Input Data
Ivan S. Maksymov
Reservoir computing (RC) systems can efficiently forecast chaotic time series using nonlinear dynamical properties of an artificial neural network of random connections. The versat…