A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Paper identifies resting positions using EGG, ECG, respiration rate, and SpO2.
BrainSurfCNN predicts task contrasts from resting-state fingerprints, improving accuracy over baseline.
ECGID research focuses on rest but not exercise, this study evaluates both.
REST improves robustness and efficiency of sleep monitoring models.
The paper tackles rested bandits with non-decreasing and concave rewards, deriving lower bounds and an efficient algorithm.
Study on spin-zero rest-mass fields using conformal geometric method.
New algorithm handles both decaying and non-decaying bandit problems.
Graph-Triggered Bandits unify rested and restless bandits with graph-defined arm interactions.
Review of machine learning methods for detecting depression from resting EEG.
Paper detects abnormalities in brain activity patterns using unsupervised learning.
FlexServe simplifies deployment of PyTorch models as REST endpoints.
Proposes SOVR loss to improve adversarial robustness by increasing logit margins.
Training of one-vs.-rest SVMs can be parallelized over the number of classes in a straight forward way. Given enough computational resources, one-vs.-rest SVMs can thus be trained on data involving a large number of classes. The same cannot be stated, however, for the so-called all-in-one SVMs, which require solving a …
Machine learning techniques have gained prominence for the analysis of resting-state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an overview of various unsupervised and supervised machine learning applications to rs-fMRI. We present a methodical taxonomy of machine learning methods in resting…
Stochastic encoding improves gender classification of brain networks from UK Biobank data.
Study predicts reaction time and vigilance variability from resting-state EEG features.
Review of machine learning methods for detecting depression from resting EEG.
This paper proposes a practical approach for automatic sleep stage classification based on a multi-level feature learning framework and Recurrent Neural Network (RNN) classifier using heart rate and wrist actigraphy derived from a wearable device. The feature learning framework is designed to extract low- and mid-level…
We present a method for fast resting-state fMRI spatial decomposi-tions of very large datasets, based on the reduction of the temporal dimension before applying dictionary learning on concatenated individual records from groups of subjects. Introducing a measure of correspondence between spatial decompositions of rest …
The functional significance of resting state networks and their abnormal manifestations in psychiatric disorders are firmly established, as is the importance of the cortical rhythms in mediating these networks. Resting state networks are known to undergo substantial reorganization from childhood to adulthood, but wheth…
REST framework predicts stock trends by considering stock-specific and related-stock events.
New algorithm identifies best arm in rested bandit setting.
REST improves robustness of black-box models to geometric transformations.
Dynamic functional connectivity (FC) has in recent years become a topic of interest in the neuroimaging community. Several models and methods exist for both functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), and the results point towards the conclusion that FC exhibits dynamic changes. The e…
Bayesian model detects altered neural circuits in MCI patients.
The paper explores maximal perturbations to hide certain attributes in data while keeping the model's performance intact.
We study the space of Killing fields on the four dimensional AdS spacetime . Two subsets and are identified: (the spinor Killing fields) is constructed from imaginary Killing spinors, and (the observer Killing fields) consists of all hypersurface orthog…
ST-GCN improves rs-fMRI prediction accuracy by modeling spatio-temporal graph connectivity.
Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g. multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate…
Novel method extracts hierarchical brain connectivity patterns from fMRI.
We consider when a smooth vector bundle endowed with a connection possesses non-trivial, local parallel sections. This is accomplished by means of a derived flag of subsets of the bundle. The procedure is algebraic and rests upon the Frobenius Theorem.
Study finds PLI functional connectivity feature superior for depression recognition.
We investigate activities that have different periods of duration. We define the profit intensity as a measure of this economic category. The profit intensity in a repeated trading has a unique property of attaining its maximum at a fixed point regardless of the shape of demand curves for a wide class of probability di…
We give a proof to the Li-Yau-Hamilton type inequality claimed by Perelman on the fundamental solution to the conjugate heat equation. The rest of the paper is devoted to improving the known differential inequalities of Li-Yau-Hamilton type via monotonicity formulae.
A rational homology sphere whose Heegaard Floer homology is the same as that of a lens space is called an L-space. We classify pretzel knots with any number of tangles which admit L-space surgeries. This rests on Gabai's classification of fibered pretzel links.
Cost overruns in transport infrastructure projects know no geographical limits, overruns are a global phenomenon. Nevertheless, the size of cost overruns varies with location. In the Netherlands, cost overruns appear to be smaller compared to the rest of the world. This paper tests whether Dutch projects perform signif…
The notion of Courant algebroid was introduced by Liu, Weinstein and Xu in 1997. Its definition consists of five axioms and an assumption for a derivation. It is shown that two of the axioms and the assumption for the derivation follow from the rest of the axioms.
MAX simplifies access to DL models for non-experts.
We construct an infinitely exchangeable process on the set $\cate$ of subsets of the power set of the natural numbers via a Poisson point process with mean measure on the power set of . Each $E\in\cate$ has a least monotone cover in $\catf$, the collection of monotone subsets of $\cate$, an…
BoFire optimizes chemistry experiments using Bayesian Optimization.
For any positive integer r, we exhibit a knot Kr with (20 2 r--1 + 1) crossings whose Jones polynomial V (Kr) is equal to 1 mod-ulo 2 r. Our construction rests on a certain 20-crossing tangle T 20 which is undetectable by the Kauffman bracket polynomial pair mod 2.
Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a c…
Simple 1-D CNNs classify Autism from rsfMRI.
I present a web service for querying an embedding of entities in the Wikidata knowledge graph. The embedding is trained on the Wikidata dump using Gensim's Word2Vec implementation and a simple graph walk. A REST API is implemented. Together with the Wikidata API the web service exposes a multilingual resource for over …
CovNet models covariance for multidimensional functional data efficiently.
Based on the notion of dilatation structure arXiv:math/0608536, we give an intrinsic treatment to sub-riemannian geometry, started in the paper arXiv:0706.3644 . Here we prove that regular sub-riemannian manifolds admit dilatation structures. From the existence of normal frames proved by Bellaiche we deduce the rest of…
Computed the 4-genus for all 12-crossing prime knots.
The aim of this paper is to propose an operational two-dimensional parametric adjustment for laws of maintenance in disability. The method suggested rests on splines in dimension 2; it is applied to a real data set, and the scale of reserving which results from it is compared with the scale of reference of the BCAC.