II.
LibraryProcess overview
Reference · livelib-process:quantum-computing--quantum-neural-network-training
Quantum Neural Network Training overview
Design and train quantum neural networks (QNNs) for machine learning tasks, addressing challenges like barren plateaus and optimizing training strategies.
Attributes
displayName
Quantum Neural Network Training
description
Design and train quantum neural networks (QNNs) for machine learning tasks,
addressing challenges like barren plateaus and optimizing training strategies.
libraryPath
library/specializations/domains/science/quantum-computing/quantum-neural-network-training.js
specialization
quantum-computing
example
const result = await orchestrate('quantum-neural-network-training', {
task: 'regression',
architecture: { layers: 4, qubits: 8 },
dataset: { X_train, y_train, X_test, y_test }
});
usesAgents
- qnn-trainer
Outgoing edges
lib_applies_to_domain1
- domain:quantum-computing·DomainQuantum Computing
lib_belongs_to_specialization1
- specialization:quantum-computing·SpecializationQuantum Computing
lib_implements_workflow1
- workflow:experiment-design·WorkflowExperiment Design
lib_involves_role1
- role:research-engineer·RoleResearch Engineer
lib_requires_skill_area3
- skill-area:mathematical-reasoning·SkillAreaMathematical Reasoning
- skill-area:compiler-implementation·SkillAreaCompiler & Interpreter Implementation
- skill-area:language-design·SkillAreaProgramming Language Design
uses_agent1
- lib-agent:quantum-computing--qnn-trainer·LibraryAgentqnn-trainer
Incoming edges
None.