Articles tagged with Bayesian Inference
The researchers developed an AI-based method that allows users to input natural language prompts about the materials they want to create and suggests optimal procedures for experiments to produce them. The method has been successfully applied to identify catalysts for turning carbon dioxide and hydrogen into carbon monoxide and water u...
Researchers at Tohoku University propose a way to detect dark matter using highly sensitive quantum devices connected in network structures. This approach outperforms traditional methods and has potential applications beyond dark matter searches.
Researchers developed a new AI model named BATMAN to improve T cell receptor therapy accuracy. The AI uses a vast database of over 22,000 TCR-peptide interactions to predict peptide binding and identify potential cancer treatments.
A study analyzed social determinants' impact on mental health, identifying variables that predict problems, such as physical health, loneliness, and satisfaction. Implementing policies like financial stability, local community engagement, and volunteering may reduce mental illness rates by up to 3 percentage points.
Astrophysicist Kyu-Hyun Chae develops a new method to measure gravity with 3D velocities of wide binary stars, confirming modified gravity at low acceleration. The results show that standard gravity is outside the 99.997% probability range for internal accelerations below 1 nm/s^2.
Researchers created a timeline for bacterial evolution and oxygen adaptation using genomic data, fossils, and Earth's geochemical history. Their findings suggest that some bacteria could use trace oxygen long before evolving photosynthesis.
The study investigates how the brain perceives pain and finds that the Surprise Hypothesis better explains the mechanism. Participants in the experiment reported stronger pain when they were surprised by painful stimuli, confirming the importance of reducing the gap between expected and unexpected events.
A Cornell University research team found that strategically placing a mix of medium-speed and fast-charging stations in urban areas increases driver usage and improves investor profitability by 50-100%. The team used Bayesian optimization to analyze data from Atlanta, taking into account factors like traffic and road characteristics.
A new study by MIT researchers found that debunking election misinformation is not always effective, but can be successful if people are less certain of their beliefs and believe the authority is unbiased or motivated by accuracy. The model analyzed over 200 scenarios and identified factors that make debunking efforts more successful.
Scientists analyzed millions of tweets to detect early warning signs of PTSD in COVID-19 survivors, achieving an accuracy rate of 83.29%. The study highlights the potential for machine learning techniques to identify individuals at risk of PTSD through social media data.
The study analyzed over 1.8 million SARS-CoV-2 genome sequences to track virus variant spread and evolution. The introduction of free rapid antigen tests, mask regulations, and movement restrictions led to a significant decline in new variants entering Germany.
A new study reveals the continuous evolutionary history of rice from wild to domesticated over 100,000 years, with China identified as its birthplace. The research provides new evidence for understanding the development of human society and the origins of agricultural civilization.
A new Bayesian inference framework reduces data size by over 80% while achieving accurate modeling and control of optical power evolution. The approach enables simultaneous exploitation and exploration of a data space to identify suitable candidates for autonomous driving optical networks.
A new R package, REDCapDM, enhances efficiency and reliability in managing research data collected through the popular REDCap platform. The tool provides functions for importing, transforming, identifying discrepancies, and managing data, simplifying the clinical data management process while ensuring quality and reliability.
Researchers review advances and challenges in applying SLA to evaluate unconventional reservoirs, highlighting its simplicity and convenience. The study proposes modifications to address reservoir heterogeneity and suggests combining SLA with machine learning algorithms for improved accuracy.
Researchers applied Bayesian network analysis to a corpus of 142 science fiction works, investigating the representation of extrasolar planets. They found that after the discovery of real exoplanets in 1995, fictional exoplanets became less Earth-like, reflecting the scientific reality of vast numbers of diverse exoplanet types.
Researchers have introduced an optimization technique that accelerates Bayesian inference without requiring extensive user effort. This new automated method achieves more accurate results faster than another popular approach and offers reliable uncertainty estimates to help scientists understand when to trust their predictions.
A Bayesian model analysis reveals how key covariates affect SARS-CoV-2 viral kinetics at individual and population levels. The study identifies intrinsic differences between Omicron and Delta variants, shedding light on their growth drivers.
Researchers from Boston University have developed a novel tool called DecontPro to identify and remove unwanted background noise in single-cell sequencing data. This approach enables more accurate analysis of cells and their molecular characteristics, offering new insights into diseases and conditions.
A study led by Northwestern University found that a Chicago-based community violence intervention program reduced gun violence involvement by over 73% among participants. The program's alumni showed the best outcomes, with a significant decrease in assaults, robberies, and other gun-related violence.
A new study definitively confirms the Gulf Stream has slowed by 4% over the past four decades, with implications for weather and climate. The research used Bayesian modeling to combine data from various sources, providing clear evidence of significant long-term change.
Researchers have confirmed that human brains use Bayesian inference to process visual information, allowing for precise interpretation and speed. This natural ability enables people to outperform machines in tasks such as recognizing objects in images, with implications for fields like artificial intelligence and clinical neurology.
The analysis found that aggregate federal employment remained relatively stable during the Trump presidency, but some agencies grew significantly, while others downsized or experienced major turnovers. This reflects the Trump administration's priorities, with trends aligning with its focus on immigration and federal affairs.
Researchers developed a new method using Bayesian estimation to reduce X-ray fluorescence analysis time from 7 seconds to 3 seconds per measurement point, saving up to 11 hours for large-scale elemental distributions.
A multi-institutional team has developed an efficient method for measuring high-dimensional qudits, which are more resistant to noise and can carry more information than qubits. The technique uses phase modulators and pulse shapers to characterize qudit entanglement with unprecedented precision.
A team of astronomers has developed a novel way to observe the first stars and galaxies, detecting light through the fog of the early Universe. The Square Kilometre Array will likely make images of the earliest light, but current telescopes struggle to detect the cosmological signal through hydrogen clouds.
Researchers analyzed mollusk shells at 4,000-year-old shell ring villages in Georgia and found environmental changes drove the formation and abandonment of these coastal communities. Smaller oyster shells and lower salinity conditions suggested depletion in oyster stocks and unsustainable fishing practices.
Researchers at RIKEN CBS demonstrate that neural networks minimize energy cost and solve mazes efficiently, pointing to a set of universal mathematical rules. The findings will aid in analyzing impaired brain function and generating optimized neural networks for artificial intelligences.
A new statistical analysis supports the notion that COVID-19 became more lethal in the UK in late 2020, with increased lethality attributed to factors beyond just the alpha variant of the virus. The study used Bayesian inference to draw stronger conclusions from weekly data on cases and deaths.
New study traces common ancestry of Japanese, Korean, and Tungusic languages to millet cultivation and early Amur gene pool in West Liao River region. The Farming Hypothesis is supported by linguistic, archaeological, and genetic evidence showing early farmers' spread across Northeast Asia.
A new fossil species, Taytalura alcoberi, has been discovered in Argentina's Late Triassic deposits. The 3D-preserved fossil provides insights into the early evolution of lepidosaurs, with its skull revealing a unique sphenodontian body type and dentition that differ from living or extinct groups.
Nilabja Guha, a UMass Lowell professor, received a three-year NSF grant to develop statistical tools for analyzing changes in data. The project aims to fill a gap in the analysis of changes in data and will focus on Bayesian change-point analysis.
A Bayesian statistical analysis of life's emergence and development on Earth predicts that if history were repeated, life would likely emerge similarly early. However, the emergence of intelligence might not guarantee a repeat occurrence due to its rarity.
The Argonne team applied Bayesian methods to quantify uncertainties in the thermodynamic properties of hafnium, a key component in computer electronics. They found that traditional models often lacked error bars or uncertainties, leading to inaccurate predictions.
Researchers at Tsinghua University outline recent advances on nonparametric Bayesian methods, regularized Bayesian inference, scalable algorithms, and system implementation to tackle the challenges of Big Data. They also discuss connections with deep learning and highlight the need for human expertise in devising appropriate features a...
A new study suggests that the communication between brain hemispheres is key to creativity. Highly creative individuals have significantly more nerve connections between their right and left hemispheres, particularly in the frontal lobe.
Researchers develop AI-powered system to score Wikipedia entries based on quality, outperforming human users. The algorithm uses Bayesian statistics and multivariate Gaussian distribution modeling to analyze content and rank articles accordingly.
A new statistical technique has been developed to analyze all possible causes of severity in a traffic accident. The researchers used data-mining techniques, including Latent Class Clustering and Bayesian Networks, to identify the variables that affect accident severity.
Studies show that some structural features of languages are relatively stable over time, while others exhibit individual family-specific factors. Researchers found probable connections between the Americas and NE Eurasian languages dating back to peopling of the Americas 12,000 years ago.
Researchers from Uppsala University developed new computer-based methods for Bayesian inference in evolutionary biology, enabling analysis of complex problems on ordinary desktop computers. The new methods can be applied to various fields, including species relationship reconstruction and molecular evolution studies.