粒径分布の数学的取り扱い - 第2回
粒径分布の数学的取り扱いを学び、混相流の基礎知識を深める。大阪大学名誉教授による専門的な講義で、混相流学の理解を促進。
Particle Size Distribution: Mathematical Treatment - Part 2
探索粒子尺寸分布的数学处理方法,深入了解多相流动中粒子行为的高级分析技术。
Data-Centric Engineering in Aero-Engines - Pranay Seshadri, Cambridge
Explore data-centric engineering in aero-engines, covering blade design, uncertainty estimation, and computational fluid dynamics for improved performance and reduced costs in aerospace.
Predicting What Comes Next: Modelling the COVID-19 Epidemic
Explore mathematical modeling techniques for predicting COVID-19 epidemic trends and future scenarios, with insights from public health experts.
Learning from COVID-19 Data on Transmission, Health Outcomes, Interventions and Vaccination
Explore COVID-19 data analysis on transmission, outcomes, interventions, and vaccination with Harvard researcher Xihong Lin in this insightful lecture from the Joint Mathematics Meetings.
Ideas on Conducting Experiments in AI and ML
Explore various experimental approaches in AI and ML, focusing on methodologies used in cutting-edge research and practical applications.
Statistical Methods for Medical Image Processing and Reconstruction
Explore statistical methods for medical image processing and reconstruction, from basic to advanced Bayesian approaches, across various imaging modalities.
Unbiased Learning-to-Rank Needs Unconfounded Propensity Estimation
Explore advanced techniques in unbiased learning-to-rank systems, focusing on propensity estimation methods and their impact on fair ranking algorithms and search result optimization.
Low Rank Tensor Methods in High Dimensional Data Analysis
Explore low rank tensor methods for analyzing high-dimensional data in various fields. Learn about recent progress, challenges, and applications in extracting information from multilinear arrays.
Persistent Cycle Registration and Topological Bootstrap
Novel approach for comparing persistent homology representations, utilizing spatial placement of persistent cycles. Demonstrates application in topological inference to differentiate signal from noise in point cloud data.
In Praise of Small Data - Statistical and Data Science
Explore the significance of small data in statistical and data science, emphasizing its role alongside big data in modern research and analysis methodologies.
Digital Twins in Engineering: From Air Pollution to Cardiology - Day 3
Advancing digital twins: Experts explore foundational aspects, research challenges, and key applications, bridging data-driven and mechanistic modeling for engineering and scientific domains.
Digital Twins Workshop: Foundations and Challenges - Day 1
Advancing digital twins research: Experts explore Bayesian inference, irregular posteriors, and geophysical applications in this foundational workshop for data-driven engineering.
Advances in Predictive Models for Single-cell and Regulatory Genomics
Explore cutting-edge predictive models for single-cell and regulatory genomics, enhancing understanding of cancer progression and potential treatment approaches.
Interactive Session on Data Analysis - Lecture 2
Hands-on data analysis session exploring techniques and tools for probing hadron structure at the Electron-Ion Collider, emphasizing practical skills and real-world applications.
When AI Became ML, and Then AI Again - Tracing the Evolution of Terms and Technologies
Explore the evolution of AI and ML terminology, from early ambitious goals to specialized algorithms, and their recent convergence, reflecting the field's dynamic nature and growing demand for specialized infrastructure.
A Gateway to Trustworthy AI: Using Visual Analytics to Unmask Coincidental Correlations
Explore visual analytics techniques to identify and address spurious correlations in AI systems, enhancing trustworthiness and reliability in machine learning and data-driven decision-making.
Data-Driven Insights for Drug Kinetics and Dynamics in Therapeutic Strategies
Explore how data-driven approaches and advanced statistical methods optimize drug behavior analysis and therapeutic strategies for personalized healthcare outcomes and improved treatment effectiveness.
Research Integrity: Statistical Methods for Monitoring Data Integrity - Part 1
Discover statistical methods for monitoring data integrity in research, focusing on techniques to identify truthful results and detect potential research misconduct in clinical trials.
Issues with Deconvolution Using Single-Cell Profiles - CGSI 2024
Explore challenges in deconvolution using single-cell profiles, examining key issues and potential solutions in computational genomics.
Methods for Analyzing Biobank Data: Statistical, Computational, and Privacy Challenges
Explore statistical, computational, and privacy challenges in analyzing biobank data. Learn scalable methods for estimating SNP heritability, variance components, and gene-environment interactions in complex traits.