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Quantum Implicit Neural Representations
This module implements cutting-edge Quantum Implicit Neural Representations (QINRs) that leverage quantum computing principles to represent continuous signals with unprecedented efficiency and quality. Unlike classical INRs, QINRs can achieve exponential compression ratios and superior approximation capabilities through quantum superposition and entanglement.
Key Features:
- Quantum coordinate networks with quantum positional encoding
- Quantum SIREN with quantum sinusoidal activations
- Multi-modal quantum neural fields (images, audio, 3D shapes, video)
- Quantum meta-learning for rapid adaptation to new signals
- Quantum compression with exponential storage savings
- Advanced quantum optimization techniques
Structs§
- Adaptation
Network - Adaptation
Output - Adaptation
Parameters - Adaptation
Step - Adaptive
Compression Strategy - Coherence
Tracker - Component
Network - Compressed
Representation - Compression
Config - Compression
Manager - Compression
Metadata - Compression
Result - Compression
Step - Convergence
Analysis - Convergence
Criteria - Decoherence
Model - Entanglement
Manager - Entanglement
Operation - Hyper
Network Architecture - INRQuery
Output - INRTraining
Config - INRTraining
Metrics - INRTraining
Output - Learning
Rate Scheduler - Local
Minimum - Meta
Learning Config - Momentum
State - Network
Output - Optimization
Config - Optimization
Landscape - Quality
Monitor - Quantum
Activation Config - Quantum
Adaptation Metrics - Quantum
Compression State - Quantum
Coordinate Network - Quantum
Gate - Quantum
Gradient Estimator - QuantumINR
Config - Configuration for Quantum Implicit Neural Representations
- QuantumINR
Metrics - Quantum
Implicit Neural Representation - Main Quantum Implicit Neural Representation model
- Quantum
Layer - Quantum
Layer Config - Quantum
Meta Learner - Quantum
Metrics - Quantum
Network State - Quantum
Optimization State - Quantum
Optimizer - Quantum
Positional Encoder - Quantum
Positional Encoding - Quantum
Processing Output - Quantum
State Manager - Quantum
System State - Query
Quantum Metrics - Reconstruction
Instructions - Regularization
Config - Search
Space - Skip
Connection - State
Evolution - Task
Encoder
Enums§
- Adaptation
Rule - Adaptation
Strategy - Coherence
Strategy - Collision
Resolution - Composition
Strategy - Compression
Method - Compression
Strategy Type - Connection
Type - Context
Encoding - Decomposition
Method - Decompression
Step - Efficiency
Objective - Encoder
Type - Entanglement
Operation Type - Entanglement
Pattern - Frequency
Progression - Gradient
Estimation - Initialization
Strategy - Learning
Rate Schedule - Memory
Update Rule - Meta
Learning Method - Network
Specialization - Positional
Encoding Type - Pruning
Strategy - Quality
Metric - Quantization
Scheme - Quantum
Activation - Quantum
Attention Mechanism - Quantum
Convergence Metric - Quantum
Convolution Type - Quantum
Gate Type - Quantum
Hash Function - Quantum
Layer Type - Quantum
Normalization - Quantum
Optimizer Type - Quantum
Reconstruction Protocol - Quantum
Regularization - Representation
Method - Signal
Type - Variance
Reduction - Weight
Encoding Type