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.
Deep learning model extracts location references from tweets during emergencies.
Paper proposes a method to locate power grid recordings using ENF sequences.
ALIEN detects multiple small objects and estimates their pixel locations and features.
A key step to driver safety is to observe the driver's activities with the face being a key step in this process to extracting information such as head pose, blink rate, yawns, talking to passenger which can then help derive higher level information such as distraction, drowsiness, intent, and where they are looking. I…
System identifies power grid location from media recordings.
The first step of a secure communication is authenticating legible users and detecting the malicious ones. In the last recent years, some promising schemes proposed using wireless medium network's features, in particular, channel state information (CSI) as a means for authentication. These schemes mainly compare user's…
Paper presents a simple method for accurate user localization in urban areas.
Unified Siamese network for wireless positioning and channel charting.
Framework uses deep learning to analyze large documents and identify their logical structure.
ReDO extracts object masks from images without annotations.
Deep learning predicts user identity, activity, and location from Wi-Fi signals.
This study uses Twitter to analyze traveler behavior in Manhattan.
Paper proposes DRL for unsupervised IoT localization.
Generative model prices options and extracts risk-neutral densities.
The waggle dance that honeybees perform is an astonishing way of communicating the location of food source. After over 60 years of its discovery, researchers still use manual labeling by watching hours of dance videos to detect different transitions between dance components thus extracting information regarding the dis…
We leverage automatic differentiation (AD) and probabilistic programming to develop an end-to-end optimization algorithm for batch triangulation of a large number of unknown objects. Given noisy detections extracted from noisily geo-located street level imagery without depth information, we jointly estimate the number …
A model predicts building damage locations in near real-time using intensity-based features.
Recurrent Neural Network (RNN) has been successfully applied in many sequence learning problems. Such as handwriting recognition, image description, natural language processing and video motion analysis. After years of development, researchers have improved the internal structure of the RNN and introduced many variants…
Hi-RES framework extracts medical relations from articles and EHRs.
New algorithm extracts features from superpositions in machine learning models.
The paper uses 3D shapes to reveal sundial design adjustments based on latitude.
Study predicts wind energy potential in Gulf of Oman using climate models.
MIP framework improves urban flow prediction by adapting to distribution shifts.
This Perspective provides examples of current and future applications of deep learning in pharmacogenomics, including: (1) identification of novel regulatory variants located in noncoding domains and their function as applied to pharmacoepigenomics; (2) patient stratification from medical records; and (3) prediction of…
Study calculates tail risk for various mixture distributions.
Self-guidance controls image generation by extracting properties from diffusion model representations.
Achieving machine intelligence requires a smooth integration of perception and reasoning, yet models developed to date tend to specialize in one or the other; sophisticated manipulation of symbols acquired from rich perceptual spaces has so far proved elusive. Consider a visual arithmetic task, where the goal is to car…
Spatial graph representation improves GNN performance.
This paper describes the data collection effort that is part of the project Sprekend Nederland (The Netherlands Talking), and discusses its potential use in Automatic Accent Location. We define Automatic Accent Location as the task to describe the accent of a speaker in terms of the location of the speaker and its hist…
Machine learning models perform better with location coordinates alone, not Moran Eigenvectors.
Machine learning detects subhalos in lensed images with high accuracy and low false positives.
Technology offers new ways to measure the locations of the players and of the ball in sports. This translates to the trajectories the ball takes on the field as a result of the tactics the team applies. The challenge professionals in soccer are facing is to take the reverse path: given the trajectories of the ball is i…
The recent adoption of recurrent neural networks (RNNs) for session modeling has yielded substantial performance gains compared to previous approaches. In terms of context-aware session modeling, however, the existing RNN-based models are limited in that they are not designed to explicitly model rich static user-side c…
Set classification problems arise when classification tasks are based on sets of observations as opposed to individual observations. In set classification, a classification rule is trained with sets of observations, where each set is labeled with class information, and the prediction of a class label is performed a…
Exact 1-Wasserstein distance between location-scale distributions derived, with privacy effects studied.
Arctic coastal morphology is governed by multiple factors, many of which are affected by climatological changes. As the season length for shorefast ice decreases and temperatures warm permafrost soils, coastlines are more susceptible to erosion from storm waves. Such coastal erosion is a concern, since the majority of …
Study shows one-dimensional location-scale-shape models are flat in Wasserstein geometry.
Proposes a privacy framework for location traces under conditional priors.
Deep learning typically requires training a very capable architecture using large datasets. However, many important learning problems demand an ability to draw valid inferences from small size datasets, and such problems pose a particular challenge for deep learning. In this regard, various researches on "meta-learning…
We introduce an algorithm to locate contours of functions that are expensive to evaluate. The problem of locating contours arises in many applications, including classification, constrained optimization, and performance analysis of mechanical and dynamical systems (reliability, probability of failure, stability, etc.).…
New fair-by-design model reduces bias in recidivism prediction.
In this paper, we propose a classification based glottal closure instants (GCI) detection from pathological acoustic speech signal, which finds many applications in vocal disorder analysis. Till date, GCI for pathological disorder is extracted from laryngeal (glottal source) signal recorded from Electroglottograph, a d…
CitySim dataset captures vehicle trajectories for safety research.
Maximizes mutual info across views for better image representations.
User interfaces provide an interactive window between physical and virtual environments. A new concept in the field of human-computer interaction is a soft user interface; a compliant surface that facilitates touch interaction through deformation. Despite the potential of these interfaces, they currently lack a signal …
Neural connectomics has begun producing massive amounts of data, necessitating new analysis methods to discover the biological and computational structure. It has long been assumed that discovering neuron types and their relation to microcircuitry is crucial to understanding neural function. Here we developed a nonpara…
We propose channel charting (CC), a novel framework in which a multi-antenna network element learns a chart of the radio geometry in its surrounding area. The channel chart captures the local spatial geometry of the area so that points that are close in space will also be close in the channel chart and vice versa. CC w…
Empirical median performs well in estimating location with varying scales.