arXiv research

The study analyzes river water quality using statistical and machine learning methods.

Bio-oil molecule assessment is essential for the sustainable development of chemicals and transportation fuels. These oxygenated molecules have adequate carbon, hydrogen, and oxygen atoms that can be used for developing new value-added molecules (chemicals or transportation fuels). One motivation for our study stems fr…

MTL improves multi-dimensional regression in luminescence sensing.

We use a deep learning model trained only on a patient's blood oxygenation data (measurable with an inexpensive fingertip sensor) to predict impending hypoxemia (low blood oxygen) more accurately than trained anesthesiologists with access to all the data recorded in a modern operating room. We also provide a simple way…

System predicts respiratory failure up to 8 hours early.

Adaptive sampling theory has shown that, with proper assumptions on the signal class, algorithms exist to reconstruct a signal in $\mathbb{R}^{d}$ with an optimal number of samples. We generalize this problem to the case of spatial signals, where the sampling cost is a function of both the number of samples taken and t…

Study finds racial bias in pulse oximeter readings has minimal impact on ICU ventilation rates.

New method uses machine learning to analyze catalyst reactions.

This work improves the accuracy of OEF and DBV maps from qBOLD MRI data.

Tree-based model averaging improves CATE estimation from diverse sites.

Deep learning has achieved impressive prediction performance in the field of sequence learning recently. Dissolved oxygen prediction, as a kind of time-series forecasting, is suitable for this technique. Although many researchers have developed hybrid models or variant models based on deep learning techniques, there is…

We propose a simple auto-encoder framework for molecule generation. The molecular graph is first encoded into a continuous latent representation $z$, which is then decoded back to a molecule. The encoding process is easy, but the decoding process remains challenging. In this work, we introduce a simple two-step decodin…

Purpose: Optical imaging is evolving as a key technique for advanced sensing in the operating room. Recent research has shown that machine learning algorithms can be used to address the inverse problem of converting pixel-wise multispectral reflectance measurements to underlying tissue parameters, such as oxygenation. …

Develops a risk score to assist ECMO planning for critically ill patients with viral or unspecified pneumonia.

Advances of modern sensing and sequencing technologies generate a deluge of high dimensional space-temporal physiological and next-generation sequencing (NGS) data. Physiological traits are observed either as continuous random functions, or on a dense grid and referred to as function-valued traits. Both physiological a…

Novel spatio-temporal LSTM model forecasts oceanic variables across sensors and scales.

Functional connectivity refers to the temporal statistical relationship between spatially distinct brain regions and is usually inferred from the time series coherence/correlation in brain activity between regions of interest. In human functional brain networks, the network structure is often inferred from functional m…

Theory for algebraic data on categories via concentration structures.

Paper addresses concentration of distances for fractional quasi p-norms, identifying conditions for concentration and anti-concentration.

Study Finsler metric measure manifolds' concentration properties.

New method improves missing mass concentration bounds.

Surfaces in 3-manifolds concentrate at curvature critical points.

Sharp concentration bounds for i.i.d. variables.

We survey recent results related to the concentration of eigenfunctions. We also prove some new results concerning ball-concentration, as well as showing that eigenfunctions saturating lower bounds for $L^1$-norms must also, in a measure theoretical sense, have extreme concentration near a geodesic.

A new model CDTM improves text classification by concentrating document topics.

Simplified proof of Gaussian concentration inequality using covariance.

Study provides bounds for estimating intrinsic dimension using Gaussian kernels.

Developed concentrated liquidity in n-dimensional AMM with polar coordinates in Rust.

In this paper, we consider a concentration of measure problem on Riemannian manifolds with boundary. We study concentration phenomena of non-negative $1$-Lipschitz functions with Dirichlet boundary condition around zero, which is called boundary concentration phenomena. We first examine relation between boundary concen…

Study on volume of tubes and concentration in Riemannian geometry.

Polluting fine dusts in South Korea which are mainly consisted of biomass burning and fugitive dust blown from dust belt is significant problem these days. Predicting concentrations of fine dust particles in Seoul is challenging because they are product of complicate chemical reactions among gaseous pollutants and also…

This study assesses risk concentration in MDB portfolios using Monte Carlo simulations.

We study concentration phenomena of eigenfunctions of the Laplacian on closed Riemannian manifolds. We prove that the volume measure of a closed manifold concentrates around nodal sets of eigenfunctions exponentially. Applying the method of Colding and Minicozzi we also prove restricted exponential concentration inequa…

A limit point p of a discrete group of Mobius transformations acting on S^n is called a concentration point if for any sufficiently small connected open neighborhood U of p, the set of translates of U contains a local basis for the topology of S^n at p. For the case of Fuchsian groups (n = 1), every concentration point…

New approach to concentration inequalities for unbounded state space dynamical systems.

Q-learning for average cost MDPs gets a concentration bound.

Sharp concentration results for sums of heavy-tailed random variables.

The paper reviews and improves concentration inequalities for statistical inference.

Study analyzes impact of concentrated liquidity on trading fees and provider returns.

In this paper, we study the Lévy-Milman concentration phenomenon of 1-Lipschitz maps into infinite dimensional metric spaces. Our main theorem asserts that the concentration to an infinite dimensional $\ell^p$-ball with the $\ell^q$-distance function for $1\leq p<q\leq +\infty$ is equivalent to the concentration to the…

This work explores the characteristics of financial contagion in networks whose links distributions approaches a power law, using a model that defines banks balance sheets from information of network connectivity. By varying the parameters for the creation of the network, several interbank networks are built, in which …

We give concentration bounds for martingales that are uniform over finite times and extend classical Hoeffding and Bernstein inequalities. We also demonstrate our concentration bounds to be optimal with a matching anti-concentration inequality, proved using the same method. Together these constitute a finite-time versi…

New concentration inequalities for tensors with heavy-tailed coefficients.

Proves new concentration inequalities for sub-gaussian and sub-exponential variables.

Paper studies equatorial concentration of measure in sphere immersions and submersions.

Hybrid Amortized Inference improves PPG model interpretability.

Study on stock portfolio concentration among Finnish households and investors.

Multispectral optical imaging is becoming a key tool in the operating room. Recent research has shown that machine learning algorithms can be used to convert pixel-wise reflectance measurements to tissue parameters, such as oxygenation. However, the accuracy of these algorithms can only be guaranteed if the spectra acq…