Twitter-color Created with Sketch. Amazon-color Created with Sketch. Facebook-color Created with Sketch. github [#142] Created with Sketch. meta_fill Pinterest-color Created with Sketch. ProductHunt-color Created with Sketch. Spotify-color Created with Sketch. Threads Logo Streamline Icon: https://streamlinehq.com Yelp-color Created with Sketch. Youtube-color Created with Sketch.
TopAIToolsTopAITools
  • 免费工具
  • 分类
  • 排行榜
  • 优惠
  • 提交工具
ZH
TopAIToolsTopAITools
TopAI

TopAITools

TopAITools, 最佳顶级AI工具

AI 词汇表|English简体中文繁體中文한국어日本語PortuguêsEspañolDeutschFrançaisTiếng Việt|地图

© 2026 TopAITools. 保留所有权利。

关于

  • Privacy Policy
  • Terms of Service

联系我们

business@topaitoolsreview.com
首页AI 词汇表Deep Learning什么是前向传播

AI 词汇表

0-9
3D Reconstruction1-shot learning2-stage detector3D convolution4D data5G + AI6DoF pose estimation7D representation8-bit quantization9-layer network0-shot learning
A
Artificial Intelligence (AI)AlgorithmAttentionAutoencoderAGI / Artificial General IntelligenceA/B TestingAccountabilityAccuracyAcoustic ModelingActivation FunctionsActive LearningActor-Critic MethodsActuatorsAdaDeltaAdaGradAdam OptimizerAdjusted R-SquaredAdversarial AttacksAffordance LearningAgent-Based ModelingAgentic AI / Autonomous AgentsAgentic AI FrameworksAgglomerative ClusteringAI AcceleratorsAI Act (EU)AI AgentsAI AlignmentAI and BiasAI and SustainabilityAI APIsAI Art GenerationAI AssistantsAI AuditAI AuditingAI Bill of Rights (US Blueprint)AI ContainmentAI DemocratizationAI Ethics BoardsAI Ethics GuidelinesAI Feature StoreAI for Climate ChangeAI Generated ContentAI Governance FrameworksAI GuardrailsAI HallucinationsAI in Healthcare EthicsAI in WarfareAI LegislationAI LiteracyAI MarketplacesAI Model GovernanceAI Model HubAI Model RegistryAI Model WeightsAI Music GenerationAI OrchestrationAI PolicyAI RegulationsAI SafetyAI SecurityAI SingularityAI Transparency ReportAI WatermarkingAI WinterAI Workflow AutomationAI-as-a-ServiceAlan TuringAlgorithmic AccountabilityAlgorithmic Bias MitigationAlgorithmic DiscriminationAlgorithmic TransparencyAndrew NgAnomaly DetectionAnomaly Detection in SecurityAnthropicApache KafkaAPI DevelopmentAPI EndpointsApriori AlgorithmArtificial General Intelligence (AGI)Artificial Neural NetworksArtificial SuperintelligenceASICsAssociation Rule LearningAsynchronous Advantage Actor-CriticAttention MechanismsAUCAudio ClassificationAudio Signal ProcessingAugmented RealityAuthenticationAuthorizationAutoencodersAutomated ReasoningAutomatic Speech Recognition (ASR)AutomationAutoMLAutonomous NavigationAutoregressive Models
B
BERTBoostingBackpropagationBatch NormalizationBiasBag-of-Words ModelBaggingBatch SizeBayesian InferenceBayesian NetworksBayesian OptimizationBias in AIBias-Variance TradeoffBig DataBig Data TechnologiesBiometric SecurityBLEU ScoreBlockchain in AIBox PlotByte-Pair Encoding (BPE)
C
Classifier / ClassificationCross-ValidationClusteringCNN / Convolutional Neural NetworkChatbotCaffeCalculusCalibrationCalifornia Consumer Privacy Act (CCPA)Canary DeploymentCapsule NetworksCarbon Footprint of AICase-Based ReasoningCatastrophic ForgettingCentral Limit TheoremChain-of-ThoughtChinese Room ArgumentClass ImbalanceClassificationCloud AI PlatformsCloud ComputingClustering AlgorithmsCode Generation ModelsCognitive ArchitecturesCognitive ComputingCohereColab NotebooksCollaborative FilteringColor SpacesComplex AnalysisComplianceCompliance Standards (ISO IEEE)Computational ComplexityComputational Fluid DynamicsComputational Theory of MindCompute-Optimal ModelsConcept DriftConceptual GraphsConditional ProbabilityConfusion MatrixConsciousness in AIConsistency ModelsConstitutional AIConstraint Satisfaction ProblemsContainerizationContent-Based FilteringContext WindowContinual LearningContinuous Integration/Continuous Deployment (CI/CD)Control SystemsConversational AIConvolutional Neural NetworksCOPPACoreference ResolutionCorrelationCorrelation MatrixCost-Sensitive LearningCross-Entropy LossCurriculum LearningCyber Threat IntelligenceCybersecurity Regulations
D
Discriminative ModelDeterministic ModelDeep LearningData AugmentationDeepfakeDALL·EData AnnotationData CatalogData CentersData CleaningData DriftData GovernanceData IngestionData IntegrationData LabelingData LakeData LakesData LeakageData LineageData MiningData PipelineData PoisoningData PreprocessingData PrivacyData ProtectionData Protection LawsData QualityData SecurityData SovereigntyData TransformationData VersioningData VisualizationData Visualization TechniquesData WarehousingDatabases for AIDavies-Bouldin IndexDBSCANDecision Boundary VisualizationDecision TreesDeep Belief NetworksDeep Q-NetworksDeep Reinforcement LearningDeepfakesDeepMindDemis HassabisDependency ParsingDepth EstimationDescriptive StatisticsDialogue SystemsDifferential EquationsDifferential EvolutionDifferential PrivacyDiffusion ModelsDigital DivideDigital ProvenanceDigital TwinsDimensionality ReductionDirect Preference Optimization (DPO)Discourse AnalysisDiscrete Event SimulationDiscrete MathematicsDisinformationDistributed ComputingDistributed File SystemsDistributed TrainingDockerDronesDropoutDropout RegularizationDynamical Systems
E
EpochEncoderEnsemble LearningExplainable AI (XAI)EmbeddingEarly StoppingEdge AIEdge ComputingEdge DetectionEigenvalues and EigenvectorsElon MuskEmbedding SizeEmbeddingsEmbodied AIEmergent AbilitiesEmotion RecognitionEnsemble MethodsEpisodic MemoryEthical AIEthical AI GuidelinesEthical AuditingEthical Decision-MakingEthical DilemmasEthical FrameworksEthics of AIETL ProcessesEvolutionary AlgorithmsExistential RiskExpectation-MaximizationExpectation-Maximization AlgorithmExpected Calibration ErrorExpert SystemsExplainabilityExploration vs. ExploitationExploratory Data AnalysisExport Controls
F
Foundation ModelForward PropagationFusion / Multimodal FusionFeature ExtractionFine-tuningF1 ScoreFacial RecognitionFairnessFastAIFeature EngineeringFeature ImportanceFeature SelectionFeature StoreFeature StoresFederated LearningFei-Fei LiFew-Shot LearningFinite Element AnalysisFirst-Order LogicFlow MatchingForce ControlFoundation Model EconomyFoundation ModelsFourier TransformFPGAsFrame LanguagesFunctional Analysis
G
GAN / Generative Adversarial NetworkGroundingGenerative AIGradient DescentGraph Neural Network (GNN)Game Playing AIGame TheoryGame Theory SimulationsGated Recurrent UnitsGaussian Mixture ModelsGeneral Data Protection Regulation (GDPR)Generative Adversarial NetworksGenerative ModelsGenetic AlgorithmsGensimGeoffrey HintonGlobal CooperationGPT ModelsGrad-CAMGradient Boosting MachinesGradient ClippingGraph Neural NetworksGraph TheoryGraphics Processing Units (GPUs)Grid Search
H
Hierarchical ModelHyperparameterHallucinationHeuristicHidden LayerHadoopHeatmapHelpHeuristic AlgorithmsHidden Markov ModelsHierarchical Reinforcement LearningHigh-Performance ComputingHIPAAHistogramHOGHPC ClustersHugging FaceHugging Face TransformersHuman RightsHuman-in-the-LoopHuman-Robot InteractionHyperparameter OptimizationHyperparameter Tuning
I
InterpretabilityInstruction tuningImbalanced DataInstance / SampleIntelligence Amplification / AugmentationIlya SutskeverImage CaptioningImage ClassificationImage RecognitionImage SegmentationImpact on EmploymentIn-Context LearningIndustrial RobotsInferenceInference EnginesInference OptimizationInferential StatisticsInformation TheoryInformed ConsentInfrastructure as CodeInstance SegmentationIntellectual Property RightsIntelligent AgentsIntrusion Detection SystemsInverse Reinforcement Learning
J
JAXJSONL / JSON-linesJuxtapositionJitteringJoint EmbeddingJohn McCarthyJoint Probability DistributionJuergen SchmidhuberJupyter Notebooks
K
K-Shot LearningKernel TrickKL Divergence (Kullback–Leibler Divergence)Knowledge DistillationK-means ClusteringK-Nearest NeighborsKai-Fu LeeKalman FiltersKerasKnowledge CutoffKnowledge GraphsKnowledge RepresentationKubernetes
L
LSTM / Long Short-Term MemoryLarge Language Model (LLM)Latent VariableLoss FunctionLearning RateL1 RegularizationL2 RegularizationLabel SmoothingLanguage ModelingLanguage ModelsLaplace TransformLarge Language Models (LLMs)Large Multimodal ModelsLatent Dirichlet AllocationLatent SpaceLaw of Large NumbersLayer NormalizationLearning CurveLearning Rate DecayLearning Rate SchedulingLemmatizationLIMELinear AlgebraLinear RegressionLog LossLogic ProgrammingLogistic RegressionLong Short-Term Memory NetworksLong-Context ModelsLoRA (Low-Rank Adaptation)
M
Multimodal / MultimodalityMulti-head AttentionMachine Learning (ML)ModelMeta-learningMachine ConsciousnessMachine TranslationMarkov Chain ModelsMarkov Chain Monte CarloMarkov Decision ProcessesMarkov ModelsMarvin MinskyMasked Language ModelsMaster Data ManagementMatplotlibMatrix DecompositionMCPMean Absolute ErrorMean Squared ErrorMechanistic InterpretabilityMel-Frequency Cepstral Coefficients (MFCCs)Metadata ManagementMicroservicesMidjourneyMind UploadingMini ToolMini-Batch Gradient DescentMixture of Experts (MoE)MLOpsMobile RobotsModel CardsModel CompressionModel DeploymentModel DriftModel Explainability ToolsModel MonitoringModel ServingModel StealingMomentum OptimizationMonitoring and LoggingMonte Carlo MethodsMonte Carlo SimulationsMoral MachinesMotion DetectionMotion PlanningMulti-Armed Bandit ProblemMultimodal AIMusic Information RetrievalMXNet
N
NLU / Natural Language UnderstandingNormalizationNeural NetworkNovelty Detection / Anomaly DetectionNLP / Natural Language Processingn-GramsNaive Bayes AlgorithmNaive Bayes ClassifierNamed Entity RecognitionNatural Language Generation (NLG)Natural Language ProcessingNatural Language Processing (NLP)Natural Language UnderstandingNesterov Accelerated GradientNetwork SimulationsNeural Architecture SearchNeural NetworksNeural Processing Unit (NPU)Neuromorphic ComputingNick BostromNLTKNoise ReductionNoSQL DatabasesNumPyNVIDIA CUDA
O
One-hot EncodingOverfittingObjective FunctionOptimizerOnline LearningObject DetectionObject TrackingOntologiesOpenAIOpenAI GPTOptical Character RecognitionOptimization TheoryOut-of-Distribution (OOD) Data
P
PromptParameterPretrainingPolicy / Reinforcement Learning PolicyPoolingPandasParallel ComputingParameter CountParameter-Efficient Fine-Tuning (PEFT)Part-of-Speech TaggingPartial Dependence PlotsPath PlanningPattern RecognitionPeople also viewedPerception in AIPerceptronPerplexityPeter NorvigPhilosophy of MindPhoneticsPipelinesPlanning and SchedulingPlotlyPolicy GradientsPolicy OptimizationPose EstimationPositional EncodingPragmaticsPrecisionPredictive ModelingPredictive ProbabilityPreference TuningPrincipal Component AnalysisPrivacyPrivacy-Preserving Machine LearningProbability Density FunctionsProbability TheoryProblem SolvingProcess ModelingProcess-Based SupervisionPrompt ChainingPrompt EngineeringPrompt InjectionPrompt MarketplacePrompt TemplatesPropositional LogicProximal Policy OptimizationPruningPyTorch
Q
Q-learningQueryQueue / BufferQuantizationQuality EstimationQLoRA (Quantized Low-Rank Adaptation)Quantum ComputingQuantum Machine LearningQuestion AnsweringQuestion Answering Systems
R
RNN / Recurrent Neural NetworkRepresentation LearningRetrieval Augmented Generation (RAG)Reinforcement Learning (RL)RegularizationR-SquaredRandom ForestsRandom SearchRay KurzweilReal AnalysisReasoning EnginesRecallRecommender SystemsRecurrent Neural NetworksRed TeamingRegressionRegression AnalysisRegulatory ComplianceReinforcement Learning from Human FeedbackReinforcement Learning in RoboticsReproducibilityResponsible AIRetrieval-Augmented GenerationReward FunctionRMSpropRobot KinematicsRobot VisionRobotic ManipulationRobotic Operating System (ROS)Robotics TransformersRobustness in AI ModelsROC CurveRodney BrooksRoot Mean Squared ErrorRule-Based Systems
S
SoftmaxSamplingSupervised LearningSequence ModelingSelf-Supervised LearningSaliency MapsSARSA AlgorithmScalable OversightScaling LawsScatter PlotScikit-LearnSciPySeabornSearch AlgorithmsSecure HardwareSecure Multi-Party ComputationSecure ProtocolsSelf-AttentionSelf-Driving CarsSemantic NetworksSemantic ParsingSemantic Role LabelingSemantic SegmentationSemantic WebSemi-Supervised LearningSensorsSentencePieceSentiment AnalysisSequence LabelingServerless ComputingServerless GPUsSet TheorySHAP ValuesSiamese NetworksSIFTSilhouette ScoreSimulated AnnealingSimulation HypothesisSimulation-to-Real Transfer (Sim2Real)Simultaneous Localization and Mapping (SLAM)SMOTESocial Acceptance of AISocial SimulationSOTA (State of the Art)spaCySparkSpeaker DiarizationSpectrogram AnalysisSpeech EnhancementSpeech RecognitionSpeech SynthesisSpiking Neural NetworksSQLStable DiffusionStackingState-Action PairsStatistical AnalysisStatistical DistributionsStatisticsStemmingStochastic Gradient DescentStochastic ModelingStochastic ProcessesStop WordsStream ProcessingStrong AIStrong vs. Weak AIStuart RussellStyle TransferSubword TokenizationSupport Vector MachinesSURFSurveillanceSwarm IntelligenceSymbolic AISynthetic Data GenerationSynthetic MediaSystem DynamicsSystem Prompt
T
TokenizerTransformerTuning / Hyperparameter TuningTransfer LearningTraining Datat-SNETeacher ForcingTechnological SingularityTeleoperationTemperatureTemporal Difference LearningTensor Processing Units (TPUs)TensorFlowTesting and ValidationText SummarizationText-to-Audio GenerationText-to-Image GenerationText-to-Speech (TTS)Text-to-Video GenerationTF-IDFTheanoTime Series AnalysisTimnit GebruTinyMLToken LimitTokenizationTokensTool Use (LLMs)Topic ModelingTopologyTransformer ModelsTransformer NetworksTransparencyTransparency RequirementsTrust Region Policy OptimizationTrustworthy AITruthfulness (in LLMs)Turing Test
U
U-NetUncertainty EstimationUnderfittingUniversal Approximation TheoremUnsupervised LearningUMAPUnmanned Aerial Vehicles (UAVs)Unmanned Ground Vehicles
V
Vision Transformer (ViT)Variational Autoencoder (VAE)Vector EmbeddingVanishing / Exploding GradientValidation SetValidation CurveValue FunctionVector DatabaseVersion Control for ModelsVibe code an AI ToolVideo Generation ModelsVirtual Reality SimulationsVoice BiometricsVoice CloningVoice Conversion
W
Weight DecayWord EmbeddingWorkflowWhitening / Whitening TransformationWeak SupervisionWarmup StepsWeak AIWord EmbeddingsWord Sense DisambiguationWordPieceWorld Models
X
X-axis / feature axisXLMXLNetXAI / Explainable AIXOR problem
Y
Yoga of AIY-transform / YUVYield (model yield / throughput)Y-axis / feature axisYAGNI (You Aren't Gonna Need It)Yann LeCunYoshua Bengio
Z
Z-score NormalizationZero-gradient phenomenonZero-shot Learning / Zero-shot inferenceZero-centric / Zero-bias initializationZygosity in augmentationZero Trust Architecture

什么是前向传播

Deep Learning
[wˌʌt ɪz fˈɔːɹwɚd pɹˌɑːpɐɡˈeɪʃən]
最后更新: 2025年10月15日

前向传播是神经网络中的一个核心概念,是训练和推理过程中的重要步骤。它指的是在神经网络中,从输入层到输出层的信号流动过程。在这一过程中,输入数据经过各个神经元的加权和激活函数,逐层传递,最终输出结果。理解这一过程对于设计有效的深度学习模型至关重要。


前向传播的重要性在于它是计算输入数据预测的基础。通过这一过程,神经网络能够生成输出,为训练提供必要的反馈。理解前向传播的工作原理是构建高效神经网络的关键。


在前向传播中,每一层的输出作为下一层的输入。每个神经元计算输入的加权和,并通过激活函数进行非线性变换。这个过程可以通过矩阵运算高效实现,尤其在大型数据集和复杂模型中。


前向传播广泛应用于图像识别、自然语言处理和推荐系统等领域。例如,在图像分类任务中,输入的图像数据会通过多个卷积层和全连接层进行前向传播,最终输出每个类别的概率分布。


随着深度学习的快速发展,前向传播的效率和准确性不断提高。研究者们正在探索更高效的计算方法和网络结构,使得前向传播能够更快地处理大规模数据。


前向传播的优点在于其直观性和高效性,能够快速计算预测结果。然而,其缺点在于依赖于网络结构的设计,过于复杂的网络可能导致过拟合问题。


在设计神经网络时,需要合理配置每层的神经元数量和激活函数,以平衡模型的表现与计算效率。

相关词条

什么是自编码器

了解自编码器:一种无监督学习算法,用于无标签的数据压缩和特征提取。

Deep Learning

什么是反向传播

了解反向传播,这一训练神经网络的基本算法及其工作原理、优缺点和未来趋势。

Deep Learning

什么是批量归一化

批量归一化是深度学习中的关键技术,提高了训练速度和稳定性,增强了模型性能,减少了过拟合。

Deep Learning

什么是深度学习

了解深度学习的概念、在人工智能中的重要性、各领域的应用及其优缺点。

Deep Learning