索引编号 | 英文术语 | 中文翻译 | 常用缩写 | 来源&扩展 | 备注 |
---|---|---|---|---|---|
AITD-00369 | Damping | 衰减 | [1] | ||
AITD-00370 | Damping Factor | 阻尼因子 | [1] | ||
AITD-00371 | Data | 数据 | [1] | ||
AITD-00372 | Data Augmentation | 数据增强 | [1] | ||
AITD-00373 | Data Generating Distribution | 数据生成分布 | [1] | ||
AITD-00374 | Data Generating Process | 数据生成过程 | [1] | ||
AITD-00375 | Data Instance | 数据样本 | [1] | ||
AITD-00376 | Data Mining | 数据挖掘 | [1] | ||
AITD-00377 | Data Parallelism | 数据并行 | [1] | ||
AITD-00378 | Data Point | 数据点 | [1] | ||
AITD-00379 | Data Preprocessing | 数据预处理 | [1] | ||
AITD-00380 | Data Set | 数据集 | [1][2] | ||
AITD-00381 | Data Wrangling | 数据整理 | [1] | ||
AITD-00382 | Dataset Augmentation | 数据集增强 | [1] | ||
AITD-00383 | Davidon-Fletcher-Powell | DFP | [1] | ||
AITD-00384 | Debugging Strategy | 调试策略 | [1] | ||
AITD-00385 | Decision Boundary | 决策边界 | [1] | ||
AITD-00386 | Decision Function | 决策函数 | [1] | ||
AITD-00387 | Decision Stump | 决策树桩 | [1] | ||
AITD-00388 | Decision Surface | 决策平面 | [1] | ||
AITD-00389 | Decision Tree | 决策树 | DT | [1][2][3][4] | |
AITD-00390 | Decoder | 解码器 | [1] | ||
AITD-00391 | Decoding | 解码 | [1] | ||
AITD-00392 | Decompose | 分解 | [1] | ||
AITD-00393 | Deconvolution | 反卷积 | [1] | ||
AITD-00394 | Deconvolutional Network | 反卷积网络 | [1] | ||
AITD-00395 | Deduction | 演绎 | [1] | ||
AITD-00396 | Deep Belief Network | 深度信念网络 | DBN | [1] | |
AITD-00397 | Deep Boltzmann Machine | 深度玻尔兹曼机 | DBM | [1] | |
AITD-00398 | Deep Circuit | 深度回路 | [1] | ||
AITD-00399 | Deep Convolutional Generative Adversarial Network | 深度卷积生成对抗网络 | DCGAN | [1] | |
AITD-00400 | Deep Feedforward Network | 深度前馈网络 | [1] | ||
AITD-00401 | Deep Generative Model | 深度生成模型 | [1] | ||
AITD-00402 | Deep Learning | 深度学习 | DL | [1][2][3][4][5] | |
AITD-00403 | Deep Model | 深度模型 | [1] | ||
AITD-00404 | Deep Network | 深度网络 | [1] | ||
AITD-00405 | Deep Neural Network | 深度神经网络 | DNN | [1][2][3][4][5][6][7] | |
AITD-00406 | Deep Q-Learning | 深度 Q 学习 | [1][2] | ||
AITD-00407 | Deep Q-Network | 深度Q网络 | DQN | [1] | |
AITD-00408 | Deep Reinforcement Learning | 深度强化学习 | [1] | ||
AITD-00409 | Deep Sequence Model | 深度序列模型 | [1] | ||
AITD-00410 | Default Rule | 默认规则 | [1] | ||
AITD-00411 | Definite Integral | 定积分 | [1] | ||
AITD-00412 | Degree Of Belief | 信任度 | [1] | ||
AITD-00413 | Delta-Bar-Delta | Delta-Bar-Delta | [1] | ||
AITD-00414 | Denoising | 去噪 | [1] | ||
AITD-00415 | Denoising Autoencoder | 去噪自编码器 | [1] | ||
AITD-00416 | Denoising Score Matching | 去躁分数匹配 | [1] | ||
AITD-00417 | Denominator Layout | 分母布局 | [1] | ||
AITD-00418 | Dense | 稠密 | [1] | ||
AITD-00419 | Density Estimation | 密度估计 | [1] | ||
AITD-00420 | Density-Based Clustering | 密度聚类 | [1] | ||
AITD-00421 | Dependency | 依赖 | [1] | ||
AITD-00422 | Depth | 深度 | [1] | ||
AITD-00423 | Derivative | 导数 | [1] | ||
AITD-00424 | Description | 描述 | [1] | ||
AITD-00425 | Design Matrix | 设计矩阵 | [1] | ||
AITD-00426 | Detailed Balance | 细致平衡 | [1] | ||
AITD-00427 | Detailed Balance Equation | 细致平衡方程 | [1] | ||
AITD-00428 | Detector Stage | 探测级 | [1] | ||
AITD-00429 | Determinant | 行列式 | [1] | ||
AITD-00430 | Deterministic | 确定性 | [1] | ||
AITD-00431 | Deterministic Model | 确定性模型 | [1] | ||
AITD-00432 | Deterministic Policy | 确定性策略 | [1] | ||
AITD-00433 | Development Set | 开发集 | [1] | ||
AITD-00434 | Diagonal Matrix | 对角矩阵 | [1] | ||
AITD-00435 | Diameter | 直径 | [1] | ||
AITD-00436 | Dictionary | 字典 | [1] | ||
AITD-00437 | Dictionary Learning | 字典学习 | [1] | ||
AITD-00438 | Differentiable Function | 可微函数 | [1] | ||
AITD-00439 | Differentiable Neural Computer | 可微分神经计算机 | [1] | ||
AITD-00440 | Differential Entropy | 微分熵 | [1] | ||
AITD-00441 | Differential Equation | 微分方程 | [1] | ||
AITD-00442 | Differentiation | 微分 | [1] | ||
AITD-00443 | Dilated Convolution | 膨胀卷积 | [1] | ||
AITD-00444 | Dimension | 维度 | [1] | ||
AITD-00445 | Dimension Reduction | 降维 | [1] | ||
AITD-00446 | Dimensionality Reduction Algorithm | 降维算法 | [1][2] | ||
AITD-00447 | Dirac Delta Function | Dirac Delta函数 | [1] | ||
AITD-00448 | Dirac Distribution | Dirac分布 | [1] | ||
AITD-00449 | Directed | 有向 | [1] | ||
AITD-00450 | Directed Acyclic Graph | 有向非循环图 | DAG | [1] | |
AITD-00451 | Directed Edge | 有向边 | [1] | ||
AITD-00452 | Directed Graph | 有向图 | [1] | ||
AITD-00453 | Directed Graphical Model | 有向图模型 | [1] | ||
AITD-00454 | Directed Model | 有向模型 | [1] | ||
AITD-00455 | Directed Separation | 有向分离 | [1] | ||
AITD-00456 | Directional Derivative | 方向导数 | [1] | ||
AITD-00457 | Dirichlet Distribution | 狄利克雷分布 | [1] | ||
AITD-00458 | Disagreement Measure | 不合度量 | [1] | ||
AITD-00459 | Disagreement-Based Methods | 基于分歧的方法 | [1] | ||
AITD-00460 | Discount Factor | 衰减系数 | [1] | ||
AITD-00461 | Discounted Return | 折扣回报 | [1] | ||
AITD-00462 | Discrete Optimization | 离散优化 | [1] | ||
AITD-00463 | Discriminant Function | 判别函数 | [1] | ||
AITD-00464 | Discriminative Approach | 判别方法 | [1] | ||
AITD-00465 | Discriminative Model | 判别式模型 | [1] | ||
AITD-00466 | Discriminative RBM | 判别RBM | [1] | ||
AITD-00467 | Discriminator | 判别器 | [1] | ||
AITD-00468 | Discriminator Network | 判别网络 | [1] | ||
AITD-00469 | Distance | 距离 | [1] | ||
AITD-00470 | Distance Measure | 距离度量 | [1] | ||
AITD-00471 | Distance Metric Learning | 距离度量学习 | [1] | ||
AITD-00472 | Distributed Representation | 分布式表示 | [1] | ||
AITD-00473 | Distribution | 分布 | [1] | ||
AITD-00474 | Diverge | 发散 | [1] | ||
AITD-00475 | Divergence | 散度 | [1] | ||
AITD-00476 | Diversity | 多样性 | [1] | ||
AITD-00477 | Diversity Measure | 多样性度量/差异性度量 | [1] | ||
AITD-00478 | Divide-And-Conquer | 分而治之 | [1] | ||
AITD-00479 | Divisive | 分裂 | [1] | ||
AITD-00480 | Domain | 领域 | [1] | ||
AITD-00481 | Domain Adaptation | 领域自适应 | [1] | ||
AITD-00482 | Dominant Eigenvalue | 主特征值 | [1] | ||
AITD-00483 | Dominant Eigenvector | 主特征向量 | [1] | ||
AITD-00485 | Dominant Strategy | 占优策略 | [1] | ||
AITD-00486 | Dot Product | 点积 | [1] | ||
AITD-00487 | Double Backprop | 双反向传播 | [1] | ||
AITD-00488 | Doubly Block Circulant Matrix | 双重分块循环矩阵 | [1] | ||
AITD-00489 | Down Sampling | 下采样 | [1] | ||
AITD-00490 | Downstream Task | 下游任务 | [1] | ||
AITD-00491 | Dropout | 暂退法 | [1] | ||
AITD-00492 | Dropout Boosting | 暂退Boosting | [1] | ||
AITD-00493 | Dropout Mask | 暂退掩码 | [1] | ||
AITD-00494 | Dropout Method | 暂退法 | [1] | ||
AITD-00495 | Dual Algorithm | 对偶算法 | [1] | ||
AITD-00496 | Dual Problem | 对偶问题 | [1] | ||
AITD-00497 | Dummy Node | 哑结点 | [1] | ||
AITD-00498 | Dying ReLU Problem | 死亡ReLU问题 | [1] | ||
AITD-00499 | Dynamic Bayesian Network | 动态贝叶斯网络 | [1] | ||
AITD-00500 | Dynamic Computational Graph | 动态计算图 | [1] | ||
AITD-00501 | Dynamic Fusion | 动态融合 | [1] | ||
AITD-00502 | Dynamic Programming | 动态规划 | [1] | ||
AITD-00503 | Dynamic Structure | 动态结构 | [1] | ||
AITD-00504 | Dynamical System | 动力系统 | [1] | ||
AITD-02171 | Data Availability | 数据可用性 | [1][2] | ||
AITD-02172 | Data Cleaning | 数据清洗 | [1][2] | ||
AITD-02173 | Data Collection | 数据采集 | [1][2][3] | ||
AITD-02174 | Data Considerations | 数据注意事项 | [1] | ||
AITD-02175 | Data Curation | 数据监管 | [1] | ||
AITD-02176 | Data Disparity | 数据差异 | [1] | ||
AITD-02177 | Data Dredging | 数据挖掘 | [1] | ||
AITD-02178 | Data Imputation | 数据填补 | [1] | ||
AITD-02179 | Data Labels | 数据标签 | [1] | ||
AITD-02180 | Data Leakage | 数据泄露 | [1] | ||
AITD-02181 | Data Pre-Processing | 数据预处理 | [1] | ||
AITD-02182 | Data Processing | 数据处理 | [1] | ||
AITD-02183 | Data Quality | 数据质量 | [1][2] | ||
AITD-02184 | Data Reduction | 数据缩减 | [1][2] | ||
AITD-02185 | Data Representation | 数据表示 | [1][2] | ||
AITD-02186 | Data Selection | 数据选择 | [1] | ||
AITD-02187 | Data Sources | 数据源 | [1] | ||
AITD-02188 | Data Splitting | 数据拆分 | [1] | ||
AITD-02189 | Data Transformation | 数据转换 | [1] | ||
AITD-02190 | Data-Driven | 数据驱动 | [1][2] | ||
AITD-02191 | Data-Driven Decision-Making | 数据驱动的决策 | [1] | ||
AITD-02192 | Data-Driven Methods | 数据驱动的方法 | [1] | ||
AITD-02193 | Data-Driven Spectral Analysis | 数据驱动的光谱分析 | [1] | ||
AITD-02194 | Data-Mining | 数据挖掘 | [1] | ||
AITD-02195 | Database | 数据库 | [1] | ||
AITD-02196 | DE Algorithm | 差分进化算法 | [1] | ||
AITD-02197 | Deeplift | DeepLift模型 | [1] | ||
AITD-02198 | Dendrogram | 树状图 | [1] | ||
AITD-02199 | Density Functional Theory | 密度泛函理论 | DFT | [1][2][3][4][5][6] | |
AITD-02200 | Density-Based Spatial Clustering Of Applications With Noise | DBSCAN密度聚类 | DBSCAN | [1] | |
AITD-02201 | Descriptor | 描述符 | [1] | ||
AITD-02202 | DFT Calculations | DFT计算 | [1] | ||
AITD-02203 | Dice Similarity | 戴斯相似度 | [1] | ||
AITD-02204 | Differential Evolution | 差分进化 | DE | [1] | |
AITD-02205 | Dimensionality Reduction | 降维 | [1] | ||
AITD-02206 | Direct Neural Network Modeling | 正向神经网络建模 | [1] | ||
AITD-02207 | Discrete Manner | 离散方式 | [1] | ||
AITD-02208 | Discrete Quanta | 离散量子 | [1] | ||
AITD-02209 | Discretization | 离散化 | [1] | ||
AITD-02210 | Distillation | 蒸馏 | [1] | ||
AITD-02211 | Dynamic Datasets | 动态数据集 | [1] | ||
AITD-02212 | Dynamic Filter Networks | 动态过滤网络 | [1] | ||
AITD-02213 | Dynamic Sampling | 动态采样 | [1] | ||
AITD-02214 | Dynamics Simulations | 动力学模拟 | [1] |