Advantages of Variance Stabilization

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Information theory has allowed us to determine the fundamental limit of various communication and algorithmic problems, e.g., the channel coding problem, the compression problem, and the hypothesis testing problem. In this work, we revisit the assumptions ...

In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...

Cells are the smallest operational units of living systems. Through synthesis of various biomolecules and exchange of signals with the environment, cells tightly regulate their composition to realize a specific functional state. The transformation of a cel ...

The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg(2) over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI ...

The recent geopolitical conflicts in Europe have underscored the vulnerability of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy systems ensuring sustainable energy supply in the future, the ...

Whereas the ability of deep networks to produce useful predictions on many kinds of data has been amply demonstrated, estimating the reliability of these predictions remains challenging. Sampling approaches such as MC-Dropout and Deep Ensembles have emerge ...

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

Two -particle Bose-Einstein momentum correlation functions are studied for charged-hadron pairs in lead -lead collisions at a center -of -mass energy per nucleon pair of .'/sNN = 5.02 TeV. The data sample, containing 4.27 x 109 minimum bias events correspo ...

We consider the problem of comparing several samples of stochastic processes with respect to their second-order structure, and describing the main modes of variation in this second order structure, if present. These tasks can be seen as an Analysis of Vari ...

Surrogate-based optimization is widely used for aerodynamic shape optimization, and its effectiveness depends on representative sampling of the design space. However, traditional sampling methods are hard-pressed to effectively sample high-dimensional desi ...

The reported rate of the occurrence of unilateral spatial neglect (USN) is highly variable likely due to the lack of validity and low sensitivity of classical tools used to assess it. Virtual reality (VR) assessments try to overcome these limitations by pr ...

We derive confidence intervals (CIs) and confidence sequences (CSs) for the classical problem of estimating a bounded mean. Our approach generalizes and improves on the celebrated Chernoff method, yielding the best closed-form "empirical-Bernstein" CSs and ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

A large variety of new physics models suggest that the rates for lepton flavour violating

b

-hadron decays may be much higher than predicted in the Standard Model, which leads to a high interest in the search for such decays. This thesis presents the se ...

Being able to work effectively in a team is a vital professional skill but how do students in different disciplines, engineering and hospitality, display their emotions when working together? We investigated their self-reported use of emotional labour stra ...

High-level waste, stemming from nuclear electricity generation poses significant environmental and safety concerns. Currently, high-level wastes are stored in interim facilities needing constant monitoring and waiting for a definitive solution. Deep geolog ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

This work studies the learning process over social networks under partial and random information sharing. In traditional social learning models, agents exchange full belief information with each other while trying to infer the true state of nature. We stud ...

A major component of human skin oil is squalene, a highly unsaturated hydrocarbon that protects the skin from atmospheric oxidants. Skin oil, and thus squalene, is continuously replenished on the skin surface. Squalene is also quickly consumed through reac ...

Advantages of Variance Stabilization

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On Speed and Advantage : Results in Information Velocity and Monitoring Problems

Gibbs sampling the posterior of neural networks

Deciphering the nature of cell state transitions in single cells using quantitative modeling of temporal dynamics

Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument

Identification of typical district configurations: A two-step global sensitivity analysis framework

ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference

Spectral Estimators for High-Dimensional Matrix Inference

Two-particle Bose-Einstein correlations and their Lévy parameters in PbPb collisions at √sNN=5.02 TeV

Transportation-based functional ANOVA and PCA for covariance operators

DiffAirfoil: An Efficient Novel Airfoil Sampler Based on Latent Space Diffusion Model for Aerodynamic Shape Optimization

An immersive virtual reality tool for assessing left and right unilateral spatial neglect

Anthony C Davison and Igor Rodionov's contribution to the Discussion of 'Estimating means of bounded random variables by betting' by Waudby-Smith and Ramdas

Reliable data-driven decision-making through optimal transport

Search for the lepton flavour violating decays B0→e±μ∓ and B0s→e±μ∓ with LHCb Run 2 data

“But of course i’m going to look happy” or “He needed to know I was angry”? Comparing use of emotional labour in teamwork in engineering and hospitality students

A FEM modelling workflow to simulate THM effects in the rock around nuclear waste packages

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Random matrix methods for high-dimensional machine learning models

Social Opinion Formation and Decision Making Under Communication Trends

Squalene Depletion in Skin Following Human Exposure to Ozone under Controlled Chamber Conditions