Total Skills
7
Author Profile: hiyenwong
Skills published by hiyenwong with real stars/downloads and source-aware metadata.
Total Stars
7
Total Downloads
0
Skills Performance
Comparison chart based on real stars and downloads signals from source data.
quantum-like-mental-markers
1
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1
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quantum-photonic-neural-networks
1
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1
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spiking-quantum-encoding
1
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1
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0
event-driven-hopfield-retrieval
1
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1
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unifying-dynamics-graph-neural-computation
1
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1
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pinn-quantum-pulse-optimization
1
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1
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quantum-cognitive-tunnelling-oscillators
1
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1
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Published Skills
quantum-like-mental-markers
Quantum-informational modeling of mental markers using the I-field (information field) approach. Applies Hilbert space formalism to model contextuality, incompatibility of mental observables, and entanglement-like correlations in cognition and decision-making. Does NOT assume physical quantum processes in the brain. Use when: quantum-like cognition, mental contextuality, decision dynamics, quantum cognition modeling, I-field theory, mental markers.
Repository SourceNeeds Review
quantum-photonic-neural-networks
Time-bin-encoded Quantum Photonic Neural Networks (QPNN) architecture. Reconfigurable nonlinear photonic circuits inspired by the brain, trained to process quantum information. Time encoding requires constant number of photonic elements regardless of network size/depth. Use when: quantum photonic circuits, time-encoded QNN, photonic neural networks, quantum dot nonlinearities, Bell-state analysis, Kerr nonlinearity.
Repository SourceNeeds Review
spiking-quantum-encoding
SPATE methodology for spiking-phase adaptive temporal encoding in quantum machine learning. Converts real-valued data into leaky integrate-and-fire spike trains and maps spike statistics to quantum rotations with temporal qubits. Use when: quantum ML encoding, spike-driven temporal encoding, quantum feature preparation, temporal qubits, QML pipeline enhancement.
Repository SourceNeeds Review
event-driven-hopfield-retrieval
Event-driven asynchronous retrieval in high-capacity kernel Hopfield networks. KLR Hopfield networks achieve P/N ≈ 30 storage capacity with asynchronous updates, enabling energy-efficient neuromorphic deployment. Event count matches initial Hamming distance — minimal spurious oscillations. Activation: Hopfield network, kernel associative memory, event-driven computation, asynchronous retrieval, neuromorphic memory, storage capacity, KLR Hopfield, margin maximization.
Repository SourceNeeds Review
unifying-dynamics-graph-neural-computation
Framework unifying dynamical systems and graph theory to mechanistically understand computation in neural networks. Uses resolvent-based multi-hop pathway analysis to recover input-output routing structure from connectivity, introduces R-RNNs with resolvent-based regularization for temporally structured sparsity. Activation: multi-hop, resolvent RNN, graph computation, neural network interpretability, structure-function mapping, temporal routing, R-RNN, network communication.
Repository SourceNeeds Review
pinn-quantum-pulse-optimization
Use Physics-Informed Neural Networks (PINNs) for quantum pulse optimization and noise-aware gate fidelity. Specifically for optimizing quantum control pulses in exchange-only spin qubit systems, handling charge noise, and maximizing gate-level fidelity through noise-averaged training. Use when: optimizing quantum pulses, PINN-based quantum control, spin qubit noise mitigation, exchange-only qubits, quantum gate pulse design, charge noise optimization, silicon spin qubits.
Repository SourceNeeds Review
quantum-cognitive-tunnelling-oscillators
Quantum-tunnelling oscillator models for cognitive modelling and neural computation. Models optical illusion perception and group decision making using quantum-mechanical agents with context-dependent transitions. Use when: quantum cognition, cognitive modelling, decision making models, optical illusion perception, group decision making, quantum neural systems, quantum-tunnelling oscillators.
Repository SourceNeeds Review