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.