The Oregon Health Insurance Experiment (OHIE) offers a unique opportunity to examine the causal relationship between Medicaid coverage and happiness among low-income adults, using an experimental design. This study leverages data from comprehensive s...
The ever-growing complexity of reinforcement learning (RL) tasks demands a distributed system to efficiently generate and process a massive amount of data. However, existing open-source libraries suffer from various limitations, which impede their pr...
A subtle difference between propositional and relational data is that in many relational models, marginal probabilities depend on the population or domain size. This paper connects the dependence on population size to the classic notion of projectivi...
Previous studies on Chinese semantic role labeling (SRL) have concentrated on single semantically annotated corpus. But the training data of single corpus is often limited. Meanwhile, there usually exists other semantically annotated corpora for Chin...
A computational workflow, also known as workflow, consists of tasks that must be executed in a specific order to attain a specific goal. Often, in fields such as biology, chemistry, physics, and data science, among others, these workflows are complex...
**Data Used**: All Performance and Usage Limits Megathread comments from September 7 to September 14 **Full list of Past Megathreads and Reports**: [https://www.reddit.com/r/ClaudeAI/wiki/megathreads...
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We present cosmological constraints from a cosmic shear analysis of the fourth data release of the Kilo-Degree Survey (KiDS-1000), doubling the survey area with nine-band optical and near-infrared photometry with respect to previous KiDS analyses. Ad...
We present redshift distribution estimates of galaxies selected from the fourth data release of the Kilo-Degree Survey over an area of $\sim1000$ deg$^2$ (KiDS-1000). These redshift distributions represent one of the crucial ingredients for weak grav...
The Kilo Degree Survey (KiDS) is a 1500 square degree optical imaging survey with the recently commissioned OmegaCAM wide-field imager on the VLT Survey Telescope (VST). A suite of data products will be delivered to the European Southern Observatory...
Next-generation surveys such as the Euclid survey, the Legacy Survey of Space and Time (LSST), and the China Space Station Telescope (CSST) survey are expected to discover ~10^5 galaxy-galaxy scale strong gravitational lenses. This motivates the deve...
Neural implicit k-space representations (NIK) have shown promising results for dynamic magnetic resonance imaging (MRI) at high temporal resolutions. Yet, reducing acquisition time, and thereby available training data, results in severe performance d...
Claude is Anthropic's AI, built for problem solvers. Tackle complex challenges, analyze data, write code, and think through your hardest work.
This paper studies how gifts - monetary or in-kind payments - from drug firms to physicians in the US affect prescriptions and drug costs. We estimate heterogeneous treatment effects by combining physician-level data on antidiabetic prescriptions and...
Dubai is rapidly positioning itself as a global hub for artificial intelligence, with businesses across industries exploring ways to automate operations, enhance customer experiences, and use data mor...
With Company2Vec, the paper proposes a novel application in representation learning. The model analyzes business activities from unstructured company website data using Word2Vec and dimensionality reduction. Company2Vec maintains semantic language st...
The color-magnitude diagrams (CMDs) of three intermediate-age LMC clusters, NGC 2173, SL556 and NGC2155 are analyzed to determine their age and metallicity basing on Padova stellar models. Synthetic CMDs are compared with cluster data. The best mat...
We show that a right-handed stop in the 200-400 GeV mass range, together with a nearly degenerate neutralino and, possibly, a gluino below 1.5 TeV, follows from reasonable assumptions, is consistent with present data, and offers interesting discovery...
Distilling the thinking traces of a Large Language Model (LLM) with reasoning capabilities into a smaller model has been proven effective. Yet, there is a scarcity of work done on how model performances scale with the quantity of distillation data. I...
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