Boburmirzo/genetic-Meyer-Packard-Algorithm
Predicting a Stock Price Using a Genetic Algorithm (⭐ 16)
Predicting Thrombectomy Recanalization from CT Imaging Using Deep Learning Models
For acute ischemic stroke (AIS) patients with large vessel occlusions, clinicians must decide if the benefit of mechanical thrombectomy (MTB) outweighs the risks and potential complications following an invasive procedure. Pre-treatment computed tomo...
Predicting Business Angel Early-Stage Decision Making Using AI
External funding is crucial for early-stage ventures, particularly technology startups that require significant R&D investment. Business angels offer a critical source of funding, but their decision-making is often subjective and resource-intensive f...
KPIs Aren’t Just About Assessing Past Performance
Sep 23, 2021 · Many companies track KPIs as a way of predicting performance. To really exploit the predictive power of KPIs, though, you need to map how the KPIs for your key stakeholders feed into …
Predicting the Spatially Varying Infection Risk in Indoor Spaces Using an Efficient Airbor…
We develop a spatially dependent generalisation to the Wells-Riley model and its extensions applied to COVID-19, that determines the infection risk due to airborne transmission of viruses. We assume that the concentration of infectious particles is g...
The Magnitude and Frequency Variations of Vector-Borne Infections Outbreaks with the Ross-…
It is possible to model vector-borne infection using the classical Ross-Macdonald model. This attempt, however fails in several respects. First, using measured (or estimated) parameters, the model predicts a much greater number of cases than what is...
TITAN: Future Forecast using Action Priors
We consider the problem of predicting the future trajectory of scene agents from egocentric views obtained from a moving platform. This problem is important in a variety of domains, particularly for autonomous systems making reactive or strategic dec...
Sleep deprivation linked to false confession in new study. Legal experts are predicting it…
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Leveraging Historical Associations between Requirements and Source Code to Identify Impact…
As new requirements are introduced and implemented in a software system, developers must identify the set of source code classes which need to be changed. Therefore, past effort has focused on predicting the set of classes impacted by a requirement....
Predicting the linear response of self-gravitating stellar spheres and discs with LinearRe…
We present LinearResponse.jl, an efficient, versatile public library written in julia to compute the linear response of self-gravitating (3D spherically symmetric) stellar spheres and (2D axisymmetric razor-thin) discs. LinearResponse.jl can scan the...
TailorNet: Predicting Clothing in 3D as a Function of Human Pose, Shape and Garment Style
In this paper, we present TailorNet, a neural model which predicts clothing deformation in 3D as a function of three factors: pose, shape and style (garment geometry), while retaining wrinkle detail. This goes beyond prior models, which are either sp...
Characterizing and Predicting Supply-side Engagement on Crowd-contributed Video Sharing Pl…
Video sharing and entertainment websites have rapidly grown in popularity and now constitute some of the most visited websites on the Internet. Despite the active user engagement on these online video-sharing platforms, most of recent research on onl...
faizelkhan/Insurance-Claim-Using-Machine-Learning-
Predicting property and casualty insurance claims: A Machine Learning Approach (⭐ 6)
iTARGET: Interpretable Tailored Age Regression for Grouped Epigenetic Traits
Accurately predicting chronological age from DNA methylation patterns is crucial for advancing biological age estimation. However, this task is made challenging by Epigenetic Correlation Drift (ECD) and Heterogeneity Among CpGs (HAC), which reflect t...
Beyond Views: Measuring and Predicting Engagement in Online Videos
The share of videos in the internet traffic has been growing, therefore understanding how videos capture attention on a global scale is also of growing importance. Most current research focus on modeling the number of views, but we argue that video e...
[MacMahon] Doncic would be eligible to sign a 5YR/$345M extension in the summer. That deal…
Source: https://www.espn.com/nba/story/_/id/47014061/inside-mavericks-power-struggle-nico-harrison-vs-mark-cuban > Harrison built his case from a business perspective. Doncic would be eligible to ...
Metropolitan Scale and Longitudinal Dataset of Anonymized Human Mobility Trajectories
Modeling and predicting human mobility trajectories in urban areas is an essential task for various applications. The recent availability of large-scale human movement data collected from mobile devices have enabled the development of complex human m...
Deep Learning and Large Language Models for Audio and Text Analysis in Predicting Suicidal…
Suicide is a pressing global issue, demanding urgent and effective preventive interventions. Among the various strategies in place, psychological support hotlines had proved as a potent intervention method. Approximately two million people in China a...
An Exploratory Deep Learning Approach for Predicting Subsequent Suicidal Acts in Chinese P…
Psychological support hotlines are an effective suicide prevention measure that typically relies on professionals using suicide risk assessment scales to predict individual risk scores. However, the accuracy of scale-based predictive methods for suic...
MaskBeat: Loopable Drum Beat Generation
We present MaskBeat, a transformer-based approach for loopable drum pattern generation. Rather than predicting drum hits sequentially, our method uses bidirectional attention with iterative refinement, allowing instruments to be generated in parallel...
A marginal modelling approach for predicting wildfire extremes across the contiguous Unite…
This paper details a methodology proposed for the EVA 2021 conference data challenge. The aim of this challenge was to predict the number and size of wildfires over the contiguous US between 1993 and 2015, with more importance placed on extreme event...
Stock mechanics: theory of conservation of total energy and predictions of coming short-te…
Predicting absolute magnitude of fluctuations of price, even if their sign remains unknown, is important for risk analysis and for option prices. In the present work, we display our predictions about absolute magnitude of daily fluctuations of the...
An Algorithm Based on a Cable-Nernst Planck Model Predicting Synaptic Activity throughout…
Recent technological advances have enabled the recording of neurons in intact circuits with a high spatial and temporal resolution, creating the need for modeling with the same precision. In particular, the development of ultra-fast two-photon micros...
borisbanushev/stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and…
A Distance Measure for the Analysis of Polar Opinion Dynamics in Social Networks
Analysis of opinion dynamics in social networks plays an important role in today's life. For applications such as predicting users' political preference, it is particularly important to be able to analyze the dynamics of competing opinions. While obs...
Predicting biosignatures for nutrient limited biospheres
With the characterisations of potentially habitable planetary atmospheres on the horizon, the search for biosignatures is set to become a major area of research in the coming decades. To understand the atmospheric characteristics that might indicate...
Edinburgh Clinical NLP at SemEval-2024 Task 2: Fine-tune your model unless you have access…
The NLI4CT task assesses Natural Language Inference systems in predicting whether hypotheses entail or contradict evidence from Clinical Trial Reports. In this study, we evaluate various Large Language Models (LLMs) with multiple strategies, includin...
Yellow and Red Supergiants in the Large Magellanic Cloud
Due to their transitionary nature, yellow supergiants provide a critical challenge for evolutionary modeling. Previous studies within M31 and the SMC show that the Geneva evolutionary models do a poor job at predicting the lifetimes of these short-li...
Predicting Chroma from Luma in AV1
Chroma from luma (CfL) prediction is a new and promising chroma-only intra predictor that models chroma pixels as a linear function of the coincident reconstructed luma pixels. In this paper, we present the CfL predictor adopted in Alliance Video 1 (...
DIVINE: Coordinating Multimodal Disentangled Representations for Oro-Facial Neurological D…
In this study, we present a multimodal framework for predicting neuro-facial disorders by capturing both vocal and facial cues. We hypothesize that explicitly disentangling shared and modality-specific representations within multimodal foundation mod...
lozuponelab/AMON
Annotation of Metabolite Origin via Networks: A tool for predicting putative metabolite origins for microbes or between microbes and host with or without metabolomics data (⭐ 25)
Graph2MDA: a multi-modal variational graph embedding model for predicting microbe-drug ass…
Accumulated clinical studies show that microbes living in humans interact closely with human hosts, and get involved in modulating drug efficacy and drug toxicity. Microbes have become novel targets for the development of antibacterial agents. Theref...
Modeling the consequences of tongue surgery on tongue mobility
This paper presents the current achievements of a long term project aiming at predicting and assessing the impact of tongue and mouth floor surgery on tongue mobility. The ultimate objective of this project is the design of a software with which su...
The R Package knnwtsim: Nonparametric Forecasting With a Tailored Similarity Measure
The R package knnwtsim provides functions to implement k nearest neighbors (KNN) forecasting using a similarity metric tailored to the forecasting problem of predicting future observations of a response series where recent observations, seasonal or p...
Predicting Exporters with Machine Learning
In this contribution, we exploit machine learning techniques to evaluate whether and how close firms are to becoming successful exporters. First, we train and test various algorithms using financial information on both exporters and non-exporters in...
A Machine Learning Approach to Predicting Single Event Upsets
A single event upset (SEU) is a critical soft error that occurs in semiconductor devices on exposure to ionising particles from space environments. SEUs cause bit flips in the memory component of semiconductors. This creates a multitude of safety haz...
Characterizing, Detecting, and Predicting Online Ban Evasion
Moderators and automated methods enforce bans on malicious users who engage in disruptive behavior. However, malicious users can easily create a new account to evade such bans. Previous research has focused on other forms of online deception, like th...
predicting - WordReference.com Dictionary of English
To predict is usually to foretell with precision of calculation, knowledge, or shrewd inference from facts or experience: The astronomers can predict an eclipse; it may, however, be used without the …
Bellwether Trades: Characteristics of Trades influential in Predicting Future Price Moveme…
In this study, we leverage powerful non-linear machine learning methods to identify the characteristics of trades that contain valuable information. First, we demonstrate the effectiveness of our optimized neural network predictor in accurately predi...
Predicting Friction System Performance with Symbolic Regression and Genetic Programming wi…
Friction systems are mechanical systems wherein friction is used for force transmission (e.g. mechanical braking systems or automatic gearboxes). For finding optimal and safe design parameters, engineers have to predict friction system performance. T...