| 1 | 2D Qsar Models | 二维定量构效关系模型 |
| 2 | 3D Cartesian | 三维笛卡尔(坐标) |
| 3 | 3D Conformation | 三维构象 |
| 4 | 3D Grids | 三维(坐标)网格 |
| 5 | 3D Qsar Models | 三维定量构效关系模型 |
| 6 | Aberration-Corrected | 像差矫正 |
| 7 | Accuracy | 准确率 |
| 8 | Activation Function | 激活函数 |
| 9 | Active Learning | 主动学习 |
| 10 | Active Machine Learning | 主动机器学习 |
| 11 | Adaptive Fuzzy Neural Network | 自适应模糊神经网络 |
| 12 | Adaptive Neuro Fuzzy Inference System | 自适应神经模糊推理系统 |
| 13 | Adaptive Sampling | 自适应采样 |
| 14 | Admet Evaluation | 毒性评估 |
| 15 | Alexnet | AlexNet |
| 16 | Alphago | 阿尔法狗 |
| 17 | Approximate Probabilistic Models | 近似概率模型 |
| 18 | Area Under ROC Curve | AUC(ROC曲线下方面积,度量分类模型好坏的标准) |
| 19 | Artificial Intelligence | 人工智能 |
| 20 | Artificial Neural Network | 人工神经网络 |
| 21 | Artificial Neurons | 人工神经元 |
| 22 | Artificial Synapses | 人工突触 |
| 23 | Attention | 注意力 |
| 24 | Attention-Based | 基于注意力(机制)的 |
| 25 | Automating Synthetic Planning | 自动化综合规划 |
| 26 | Automation | 自动化 |
| 27 | Autonomous Decision-Making | 自主决策 |
| 28 | B-Clustering Algorithms | B树聚类算法 |
| 29 | Back Propagation | 反向传播 |
| 30 | Bagging | 袋装 |
| 31 | Balanced Accuracy | 平衡精度 |
| 32 | Bandgap Energy | 带隙能量 |
| 33 | Baseline | 基准 |
| 34 | Baseline Test | 基准测试 |
| 35 | Basin Hopping | 盆地跳跃(算法) |
| 36 | Bayesian Approach | 贝叶斯方法 |
| 37 | Bayesian Induction | 贝叶斯归纳 |
| 38 | Bayesian Inference | 贝叶斯推断 |
| 39 | Bayesian Mcmc Methods | 贝叶斯马尔可夫链蒙特卡洛方法 |
| 40 | Bayesian Methods | 贝叶斯方法 |
| 41 | Bayesian Molecular | 贝叶斯分子(设计方法) |
| 42 | Bayesian Network | 贝叶斯网/贝叶斯网络 |
| 43 | Bayesian Prior | 贝叶斯先验 |
| 44 | Bayesian Program Learning | 贝叶斯程序学习 |
| 45 | Bayesian Regularized Neural Network | 贝叶斯正则化神经网络 |
| 46 | Beam-Scanning | 波束扫描 |
| 47 | Bernoulli Distribution | 伯努利分布 |
| 48 | Best Separates | 最优分离 |
| 49 | Bias | 偏差/偏置 |
| 50 | Biased | 有偏 |
| 51 | Biased Dataset | 有偏数据集 |
| 52 | Bit Collisions | 字节碰撞/冲突 |
| 53 | Black Box | 黑盒子 |
| 54 | Black-Box Attack | 黑盒攻击 |
| 55 | Bonding Environments | 成键环境 |
| 56 | Bonferroni Correction | 邦弗朗尼校正 |
| 57 | Boosting | Boosting(一种模型训练加速方式) |
| 58 | Bootstrap Aggregation | 引导聚合 |
| 59 | Bottom-Up | 自下而上 |
| 60 | Broyden–Fletcher–Goldfarb–Shanno | BFGS(算法) |
| 61 | Buchwald−Hartwig Cross-Coupling | Buchwald–Hartwig 偶联(反应) |
| 62 | C4.5 Algorithm | C4.5 算法 |
| 63 | CASP | 国际蛋白质结构预测竞赛 |
| 64 | Calculation Uncertainties | 计算不确定性 |
| 65 | Canonical Ml Methods | 经典机器学习方法 |
| 66 | Cartesian Distance Vector | 笛卡尔距离向量 |
| 67 | Categorical Data | 分类数据 |
| 68 | Categorization Algorithms | 分类算法 |
| 69 | ChemDataExtractor | 化学数据提取器 |
| 70 | Chi-Squared | 卡方(分布) |
| 71 | Classification | 分类 |
| 72 | Classification And Regression Tree | 分类与回归树 |
| 73 | Classification Model | 分类模型 |
| 74 | Cluster | 簇 |
| 75 | Cluster Resolution Feature Selection | 聚类分辨率特征选择 |
| 76 | Cluster-Based Splitting | 基于聚类的分离方法 |
| 77 | Clustering Methods | 聚类方法 |
| 78 | Code Pipeline | 代码流水线 |
| 79 | Coefficient of Determination | 决定系数 |
| 80 | Combined Gradient | 组合梯度(算法) |
| 81 | Complex Data | 复合数据 |
| 82 | Computational Cost | 计算成本 |
| 83 | Computational Optimisation | 计算优化 |
| 84 | Computational Science | 计算科学 |
| 85 | Computational Toxicology | 计算毒理学 |
| 86 | Computer Science | 计算机科学 |
| 87 | Computer Simulations | 计算机模拟 |
| 88 | Computer Vision | 计算机视觉 |
| 89 | Computer-Aided | 计算机辅助 |
| 90 | Confusion Matrix | 混淆矩阵 |
| 91 | Conjugate Gradient | 共轭梯度 |
| 92 | Constraint | 约束 |
| 93 | Core-Loss Spectrum | (电子能量损失谱中的)高能区域 |
| 94 | Correlation | 相关系数 |
| 95 | Cost Function | 代价函数 |
| 96 | Coulomb Matrix | 库仑矩阵 |
| 97 | Coupled-Cluster Predictions | 耦合簇预测 |
| 98 | Covariance | 协方差 |
| 99 | Covariance Matrix | 协方差矩阵 |
| 100 | Cross-Validated Coefficient of Determination | 交叉验证的决定系数 |
| 101 | Cross-Validation | 交叉验证 |
| 102 | Crowd-Sourcing | 众包 |
| 103 | Cut-Points | 切点 |
| 104 | Cutoff Radial Function | 截断径向函数 |
| 105 | DE Algorithm | 差分进化算法 |
| 106 | DFT Calculations | DFT计算 |
| 107 | Data Augmentation | 数据增强 |
| 108 | Data Availability | 数据可用性 |
| 109 | Data Cleaning | 数据清洗 |
| 110 | Data Collection | 数据采集 |
| 111 | Data Considerations | 数据注意事项 |
| 112 | Data Curation | 数据监管 |
| 113 | Data Disparity | 数据差异 |
| 114 | Data Dredging | 数据挖掘 |
| 115 | Data Imputation | 数据填补 |
| 116 | Data Labels | 数据标签 |
| 117 | Data Leakage | 数据泄露 |
| 118 | Data Mining | 数据挖掘 |
| 119 | Data Pre-Processing | 数据预处理 |
| 120 | Data Processing | 数据处理 |
| 121 | Data Quality | 数据质量 |
| 122 | Data Reduction | 数据缩减 |
| 123 | Data Representation | 数据表示 |
| 124 | Data Selection | 数据选择 |
| 125 | Data Set | 数据集 |
| 126 | Data Sources | 数据源 |
| 127 | Data Splitting | 数据拆分 |
| 128 | Data Transformation | 数据转换 |
| 129 | Data-Driven | 数据驱动 |
| 130 | Data-Driven Decision-Making | 数据驱动的决策 |
| 131 | Data-Driven Methods | 数据驱动的方法 |
| 132 | Data-Driven Spectral Analysis | 数据驱动的光谱分析 |
| 133 | Data-Mining | 数据挖掘 |
| 134 | Database | 数据库 |
| 135 | Decision Tree | 决策树 |
| 136 | Deep Learning | 深度学习 |
| 137 | Deep Neural Network | 深度神经网络 |
| 138 | Deep Reinforcement Learning | 深度强化学习 |
| 139 | Deeplift | DeepLift模型 |
| 140 | Dendrogram | 树状图 |
| 141 | Density Functional Theory | 密度泛函理论 |
| 142 | Density-Based Spatial Clustering Of Applications With Noise | DBSCAN密度聚类 |
| 143 | Descriptor | 描述符 |
| 144 | Dice Similarity | 戴斯相似度 |
| 145 | Differential Evolution | 差分进化 |
| 146 | Dimension Reduction | 降维 |
| 147 | Dimensionality Reduction | 降维 |
| 148 | Dimensionality Reduction Algorithm | 降维算法 |
| 149 | Direct Neural Network Modeling | 正向神经网络建模 |
| 150 | Discrete Manner | 离散方式 |
| 151 | Discrete Quanta | 离散量子 |
| 152 | Discretization | 离散化 |
| 153 | Distillation | 蒸馏 |
| 154 | Dynamic Datasets | 动态数据集 |
| 155 | Dynamic Filter Networks | 动态过滤网络 |
| 156 | Dynamic Sampling | 动态采样 |
| 157 | Dynamics Simulations | 动力学模拟 |
| 158 | Eigenfunction | 特征函数 |
| 159 | Electronegativity | 电负性 |
| 160 | Elman | 埃尔曼 |
| 161 | Empirical Models | 经验模型 |
| 162 | Encoder-Decoder | 编码器-解码器(模型) |
| 163 | Energy Derivatives | 能源衍生品 |
| 164 | Energy Potentials | 能量潜力 |
| 165 | Ensemble Methods | 集成方法 |
| 166 | Entity Normalisation | 实体规范化 |
| 167 | Error Function | 误差函数 |
| 168 | Estimator | 估计/估计量 |
| 169 | Ethical Considerations | 道德考虑 |
| 170 | Euclidean Distances | 欧几里得距离 |
| 171 | Evolutionary Algorithms | 进化算法 |
| 172 | Evolutionary Method | 进化方法 |
| 173 | Exchange–Correlation | 交换关联(的能量/泛函) |
| 174 | Excited-State Potentials | 激发态能量 |
| 175 | Expected Reduction In Distortion | 符合预期的失真减少 |
| 176 | Experimental Validation Data | 实验验证数据 |
| 177 | Expert Systems | 专家系统 |
| 178 | Extended-Connectivity Circular Fingerprint | 扩展连接环形指纹 |
| 179 | Extraction Techniques | 提取技术 |
| 180 | FAIR Data Principles | FAIR数据原则 |
| 181 | Faber-Christensen-Huang-Lilienfeld | Faber-Christensen-Huang-Lilienfeld |
| 182 | Facial Recognition | 面部识别 |
| 183 | False Negatives | 假阴性 |
| 184 | False Positives | 假阳性 |
| 185 | Fchl Representation | Fchl 表示 |
| 186 | Feature Binarization | 特征二值化 |
| 187 | Feature Engineering | 特征工程 |
| 188 | Feature Extraction | 特征抽取 |
| 189 | Feature Selection | 特征选择 |
| 190 | Feature Transform | 特征变换 |
| 191 | Feature Vectors | 特征向量 |
| 192 | Features | 特征 |
| 193 | Feed Back | 反馈 |
| 194 | Feed-Forward Neural Networks | 前馈神经网络 |
| 195 | Feedback Structure | 反馈结构 |
| 196 | Feedforward Neural Network | 前馈神经网络 |
| 197 | Final Evaluation | 最终评估 |
| 198 | Findable | Accessible |
| 199 | First-Principles | 第一性原理 |
| 200 | Flow Rate | 流速 |