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临床试验设计操作特征的Q近似
Q-approximation of operating characteristics of clinical trial designs
👁 329 📚 33
关于校正临床试验的巴伊西亚成功标准和操作特征
On the Calibration of Bayesian Success Criteria and Operating Characteristics for Clinical Trials
👁 495 📚 6
通过多分辨率预测过程组合实现可扩展和强力空间预测
Scalable and Robust Spatial Prediction via Multi-Resolution Ensembles of Predictive Processes
👁 59 📚 15
图 - 成形的反面模型:内向差异的不真实性
Graph-Informed Adversarial Modeling: Infimal Subadditivity of Interpolative Divergences
👁 241 📚 7
协会神经网络的多对一Hopfield模型
A Federated Many-to-One Hopfield model for associative Neural Networks
👁 260 📚 28
时间序列预测的深度自定义模型:进展和前景
Deep Autocorrelation Modeling for Time-Series Forecasting: Progress and Prospects
👁 27 📚 19
最小化 通用 交叉输入
Minimax Generalized Cross-Entropy
👁 87 📚 6
可解释的集群分析:包装方法
Explainable cluster analysis: a bagging approach
👁 175 📚 47
双时尺度学习动态:神经网络培训的人口观点
Two-Time-Scale Learning Dynamics: A Population View of Neural Network Training
👁 487 📚 27
预测性差异
Uncertainty Quantification Via the Posterior Predictive Variance
👁 155 📚 22
通过 Coreset 对多变量分布的可缩放学习
Scalable Learning of Multivariate Distributions via Coresets
👁 206 📚 41
解决贝克曼参数优化运输的规律性
Regularity of Solutions to Beckmann's Parametric Optimal Transport
👁 311 📚 27
有限上下文模型中超参数选择的双步相继方法
A two-step sequential approach for hyperparameter selection in finite context models
👁 449 📚 9
多维高斯混合模型的模型选择和参数估计
Model Selection and Parameter Estimation of Multi-dimensional Gaussian Mixture Model
👁 52 📚 49
Stochastic Approximation中的重发和长程依赖噪声: 有限时间分析
Heavy-Tailed and Long-Range Dependent Noise in Stochastic Approximation: A Finite-Time Analysis
👁 111 📚 12
以零取序查询方式进行近交替分泌
Alternating Diffusion for Proximal Sampling with Zeroth Order Queries
👁 353 📚 0
测试板球的增强分级系统:改造克力克的模型
An Augmented Rating System for Test cricket: adapting Glicko's model
👁 48 📚 18
CCMnet: 网络生成软件包, 带有相干类模型
CCMnet: A Software Package for Network Generation with Congruence Class Models
👁 479 📚 32
利用优势提高Bayesian模式的无U-Turn采样效率
Leveraging Sparsity to Improve No-U-Turn Sampling Efficiency for Hierarchical Bayesian Models
👁 277 📚 6
与失踪的创始人建立因果关系神经网络
Stochastic Neural Networks for Causal Inference with Missing Confounders
👁 209 📚 22
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