Sliced inverse regression for survival data

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Hazard ratios are routinely reported as effect measures in clinical trials and observational studies. However, many methodological works have raised concerns about the interpretation of hazard ratios as causal effects. These concerns are often related to t ...

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. ...

Exploiting the recent advancements in artificial intelligence, showcased by ChatGPT and DALL-E, in real-world applications necessitates vast, domain-specific, and publicly accessible datasets. Unfortunately, the scarcity of such datasets poses a significan ...

DNA methylation (DNAm) is one of the most frequently studied epigenetic mechanisms facilitating the interplay of genomic and environmental factors, which can contribute to externalizing behaviours and related psychiatric disorders. Previous epigenome-wide ...

A sample of 1.3 x 10^(5) K^(+) → π^(0)e^(+)νγ candidates with less than 1% background was collected by the NA62 experiment at the CERN SPS in 2017-2018. Branching fraction measurements are obtained at percent relative precision in three restricted kinemati ...

Domain generalization (DG) aims to learn a model from multiple training (i.e., source) domains that can generalize well to the unseen test (i.e., target) data coming from a different distribution. Single domain generalization (SingleDG) has recently emerge ...

We report the discovery of 40 new satellite dwarf galaxy candidates in the sphere of influence of the Sombrero Galaxy (M104), the most luminous galaxy in the Local Volume. Using the Subaru Hyper Suprime-Cam, we surveyed 14.4 deg(2) of its surroundings, ext ...

In the field of choice modeling, the availability of ever-larger datasets has the potential to significantly expand our understanding of human behavior, but this prospect is limited by the poor scalability of discrete choice models (DCMs): as sample sizes ...

Bioaerosols are emitted from various sources into the indoor environment and can positively and negatively impact human health. Humans are the major source of bioaerosol emissions indoors, specifically for bacteria. However, efficient sampling to guarantee ...

We present Epidemic Learning ( EL ), a simple yet powerful decentralized learning (DL) algorithm that leverages changing communication topologies to achieve faster model convergence compared to conventional DL approaches. At each round of EL, each node sen ...

Deep-learning-based digital twins (DDT) are a promising tool for data-driven system health management because they can be trained directly on operational data. A major challenge for efficient training however is that industrial datasets remain unlabeled. T ...

Self-exciting point processes, widely used to model arrival phenomena in nature and society, are often difficult to identify. The estimation becomes even more challenging when arrivals are recorded only as bin counts on a finite partition of the observatio ...

Magnetic resonance spectroscopy is a powerful, non-invasive, quantitative imaging technique that allows for the measurement of brain metabolites that has demonstrated utility in diagnosing and characterizing a broad range of neurological diseases. Its impa ...

As the data volume grows, reducing the query execution times remains an elusive goal. While approximate query processing (AQP) techniques present a principled method to trade off accuracy for faster queries in analytics, the sample creation is often consid ...

Advances in computing have enabled widespread access to pose estimation, creating new sources of data streams. Unlike mock set-ups for data collection, tapping into these data streams through on-device active learning allows us to directly sample from the ...

Caprock formations, such as shales, play a key role in safe underground CO2 storage since they serve as a hydromechanical barrier that prevents migration of the injected CO2 to the surface. While their hydromechanical response is important to ensure their ...

We use deep narrowband CaHK (F395N) imaging taken with the Hubble Space Telescope (HST) to construct the metallicity distribution function (MDF) of Local Group ultra-faint dwarf galaxy Eridanus II (Eri II). When combined with archival F475W and F814W data, ...

The material and exact shape of a nanostructure determine its optical response, which is especially strong for plasmonic metals. Unfortunately, only a few plasmonic metals are available, which limits the spectral range where these strong optical effects ca ...

We consider a setup in which confidential i.i.d. samples X1, . . . , Xn from an unknown finite-support distribution p are passed through n copies of a discrete privatization chan- nel (a.k.a. mechanism) producing outputs Y1, . . . , Yn. The channel law gua ...

We use a combination of extreme value statistics, survival analysis and computer-intensive methods to analyse the mortality of Italian and French semi-supercentenarians. After accounting for the effects of the sampling frame, extreme-value modelling leads ...

Sliced inverse regression for survival data

Chattez avec Graph Search

How hazard ratios can mislead and why it matters in practice

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Dated: Guidelines for Creating Synthetic Datasets for Engineering Design Applications

Epigenome-wide DNA methylation in externalizing behaviours: A review and combined analysis

A study of the K^(+) → π^(0)e^(+)νγ decay

Center-aware Adversarial Augmentation for Single Domain Generalization

New dwarf galaxy candidates in the sphere of influence of the Sombrero galaxy

Stochastic adaptive resampling for the estimation of discrete choice models

Comparison of two methods for bioaerosol sampling and characterization in a low-biomass chamber environment

Epidemic Learning: Boosting Decentralized Learning with Randomized Communication

A Study on Gradient-based Meta-learning for Robust Deep Digital Twins

Estimation of Self-Exciting Point Processes from Time-Censored Data

Harmonization of multi-scanner in vivo magnetic resonance spectroscopy: ENIGMA consortium task group considerations

Sampling-Based AQP in Modern Analytical Engines

VL4Pose: Active Learning Through Out-Of-Distribution Detection For Pose Estimation

Insights into the interaction of a shale with CO2

Metallicity Distribution Function of the Eridanus II Ultra-faint Dwarf Galaxy from Hubble Space Telescope Narrowband Imaging

A Low-Temperature Annealing Method for Alloy Nanostructures and Metasurfaces: Unlocking a Novel Degree of Freedom

Locally Differentially-Private Randomized Response for Discrete Distribution Learning

Human mortality at extreme age