I summarize in four slides the 40 years of development of the standard solar model that is used to predict solar neutrino fluxes and then describe the current uncertainties in the predictions. I next dispel the misconception that the p-p neutrino f...
Predictive models -- learned from observational data not covering the complete data distribution -- can rely on spurious correlations in the data for making predictions. These correlations make the models brittle and hinder generalization. One soluti...
3 days ago · The first NCAA men's tournament bracketology of March has a lot of shuffling among teams in the projected field and some changes on the bubble.
How can we predict missing values in multi-dimensional data (or tensors) more accurately? The task of tensor completion is crucial in many applications such as personalized recommendation, image and video restoration, and link prediction in social ne...
The capital market plays a vital role in marketing operations for aerospace industry. However, due to the uncertainty and complexity of the stock market and many cyclical factors, the stock prices of listed aerospace companies fluctuate significantly...
Recent advancements in Artificial Intelligence (AI) have transformed decision-making in aeronautics and aerospace. These advancements in AI have brought with them the need to understand the reasons behind the predictions generated by AI systems and m...
A key step towards understanding human behavior is the prediction of 3D human motion. Successful solutions have many applications in human tracking, HCI, and graphics. Most previous work focuses on predicting a time series of future 3D joint location...
Early exiting has demonstrated great potential in accelerating the inference of pre-trained language models (PLMs) by enabling easy samples to exit at shallow layers, eliminating the need for executing deeper layers. However, existing early exiting m...
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 (...
As the complexity of machine learning (ML) models increases, resulting in a lack of prediction explainability, several methods have been developed to explain a model's behavior in terms of the training data points that most influence the model. Howev...
Humanoid robots are designed to operate in human centered environments where they execute a multitude of challenging tasks, each differing in complexity, resource requirements, and execution time. In such highly dynamic surroundings it is desirable t...
The recent focus on microbes in human medicine highlights their potential role in the genetic framework of diseases. To decode the complex interactions among genes, microbes, and diseases, computational predictions of gene-microbe-disease (GMD) assoc...
In the study of drug function and precision medicine, identifying new drug-microbe associations is crucial. However, current methods isolate association and similarity analysis of drug and microbe, lacking effective inter-view optimization and coordi...
Bike sharing has become one of the major choices of transportation for residents in metropolitan cities worldwide. A station-based bike sharing system is usually operated in the way that a user picks up a bike from one station, and drops it off at an...
This paper presents predictions of the consequences of tongue surgery on speech production. For this purpose, a 3D finite element model of the tongue is used that represents this articulator as a deformable structure in which tongue muscles anatomy...
Many approaches have been proposed to support lossless coding within video coding standards that are primarily designed for lossy coding. The simplest approach is to just skip transform and quantization and directly entropy code the prediction residu...
We present a publicly available multimodal dataset for head and neck cancer research, comprising 1123 annotated Positron Emission Tomography/Computed Tomography (PET/CT) studies from patients with histologically confirmed disease, acquired from 10 in...
# AI Weekly Rundown From September 21 to September 28th, 2025: https://preview.redd.it/elrtyi3ezsrf1.png?width=1080&format=png&auto=webp&s=81b7c0703ebea9538e932aea4f58dc1ed7da9379 ??...
# AI Weekly Rundown From September 21 to September 28th, 2025: https://preview.redd.it/z94xr9649srf1.png?width=3000&format=png&auto=webp&s=d31306ec6ffe373ea3a5a91f1ae2d3a6b688e7ec ??...
# AI Weekly Rundown From September 21 to September 28th, 2025: ?? **U.S. Military Is Struggling to Deploy AI Weapons** ? **Apple researchers develop SimpleFold, a lightweight AI for prote...
In higher education, many institutions use algorithmic alerts to flag at-risk students and deliver advising at scale. While much research has focused on evaluating algorithmic predictions, relatively little is known about how discretionary interventi...
We examine how career concerns influence the behavior and mobility of financial advisers. Drawing on a uniquely comprehensive matched panel that combines employer-employee data with a longstanding national ranking, our study tests predictions from cl...
In the steel production domain, recycling ferrous scrap is essential for environmental and economic sustainability, as it reduces both energy consumption and greenhouse gas emissions. However, the classification of scrap materials poses a significant...
This paper studies the long-term energy management of a microgrid coordinating hybrid hydrogen-battery energy storage. We develop an approximate semi-empirical hydrogen storage model to accurately capture the power-dependent efficiency of hydrogen st...
The aim of survival analysis in healthcare is to estimate the probability of occurrence of an event, such as a patient's death in an intensive care unit (ICU). Recent developments in deep neural networks (DNNs) for survival analysis show the superior...
Accurately measuring the cycle lifetime of commercial lithium-ion batteries is crucial for performance and technology development. We introduce a novel hybrid approach combining a physics-based equation with a self-attention model to predict the cycl...
Recent advances in attention-based multiple instance learning (MIL) have improved our insights into the tissue regions that models rely on to make predictions in digital pathology. However, the interpretability of these approaches is still limited. I...
Dec 24, 2021 · exploration is one of the 5,000 most common words in modern written English. It is similar in frequency to words like activate, diet, ministry, prediction, and sole.
now that it's 2026, I will be rubbing my hands together deviously so I can live vicariously through everyone. POST UR HAULS!!! comment predictions for best swag. no prizes but you get the clout. ...
Ensemble trees are a popular machine learning model which often yields high prediction performance when analysing structured data. Although individual small decision trees are deemed explainable by nature, an ensemble of large trees is often difficul...
The Support Vector Machine (SVM) of Vapnik (1998) has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions in terms of a linear combination of kernel functions centred on a s...
Large language models (LLMs) perform very well in several natural language processing tasks but raise explainability challenges. In this paper, we examine the effect of random elements in the training of LLMs on the explainability of their prediction...
What are some hot takes or predictions you have that you truly believe can happen? Could range from a team being bounced in the Round of 64 to a Cinderella run to your championship winning team. Could...
Hello! I hope you're all doing well and that you and your family are healthy during these incredibly tough times. I missed you all very much, I apologise if this prediction seems very controversial,...