惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

GbyAI
GbyAI
B
Blog
Stack Overflow Blog
Stack Overflow Blog
量子位
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
T
Tailwind CSS Blog
MongoDB | Blog
MongoDB | Blog
小众软件
小众软件
博客园 - 三生石上(FineUI控件)
Recent Announcements
Recent Announcements
U
Unit 42
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
腾讯CDC
D
DataBreaches.Net
Microsoft Azure Blog
Microsoft Azure Blog
G
Google Developers Blog
M
MIT News - Artificial intelligence
P
Proofpoint News Feed
罗磊的独立博客
L
LangChain Blog
V
Visual Studio Blog
雷峰网
雷峰网
aimingoo的专栏
aimingoo的专栏
宝玉的分享
宝玉的分享

stat.ML updates on arXiv.org

Adaptive multi-fidelity optimization with fast learning rates Enhancing AI and Dynamical Subseasonal Forecasts with Probabilistic Bias Correction Sample Complexity Bounds for Stochastic Shortest Path with a Generative Model The Harder Path: Last Iterate Convergence for Uncoupled Learning in Zero-Sum Games with Bandit Feedback Stylistic-STORM (ST-STORM) : Perceiving the Semantic Nature of Appearance Collective Kernel EFT for Pre-activation ResNets PRIM-cipal components analysis One-Shot Generative Flows: Existence and Obstructions Structural interpretability in SVMs with truncated orthogonal polynomial kernels Amortized Optimal Transport from Sliced Potentials MinShap: A Modified Shapley Value Approach for Feature Selection Unsupervised feature selection using Bayesian Tucker decomposition Multi-User mmWave Beam and Rate Adaptation via Combinatorial Satisficing Bandits Best of both worlds: Stochastic & adversarial best-arm identification Scalable Model-Based Clustering with Sequential Monte Carlo Expert-Guided Class-Conditional Goodness-of-Fit Scores for Interpretable Classification with Informative Missingness: An Application to Seismic Monitoring Lightweight Geometric Adaptation for Training Physics-Informed Neural Networks Gating Enables Curvature: A Geometric Expressivity Gap in Attention Zeroth-Order Optimization at the Edge of Stability Differentially Private Conformal Prediction CLion: Efficient Cautious Lion Optimizer with Enhanced Generalization Generative Augmented Inference Improving Machine Learning Performance with Synthetic Augmentation PAC-MCTS: Bias-Aware Pruning for Robust LLM-Guided Search and Planning Path-Sampled Integrated Gradients Heat and Matérn Kernels on Matchings Doubly Outlier-Robust Online Infinite Hidden Markov Model Momentum Further Constrains Sharpness at the Edge of Stochastic Stability Multistage Conditional Compositional Optimization BOAT: Navigating the Sea of In Silico Predictors for Antibody Design via Multi-Objective Bayesian Optimization
Towards Multilevel Modelling of Train Passing Events on t...
Lawrence A. Bull, Chiho Jeon, Mark Girolami, Andrew Duncan, Jenn · 2024-03-26 · via stat.ML updates on arXiv.org

We suggest a multilevel model, to represent aggregate train-passing events from the Staffordshire bridge monitoring system. We formulate a combined model from simple units, representing strain envelopes (of each train passing) for two types of commuter train. The measurements are treated as a longitudinal dataset and represented with a (low-rank approximation) hierarchical Gaussian process. For each unit in the combined model, we encode domain expertise as boundary condition constraints and work towards a general representation of the strain response. Looking forward, this should allow for the simulation of train types that were previously unobserved in the training data. For example, trains with more passengers or freights with a heavier payload. The strain event simulations are valuable since they can inform further experiments (including FEM calibration, fatigue analysis, or design) to test the bridge in hypothesised scenarios.