Results 51 to 60 of about 761,085 (243)
We introduce AutomataGPT, a generative pretrained transformer (GPT) trained on synthetic spatiotemporal data from 2D cellular automata to learn symbolic rules. Demonstrating strong performance on both forward and inverse tasks, AutomataGPT establishes a scalable, domain‐agnostic framework for interpretable modeling, paving the way for future ...
Jaime A. Berkovich +2 more
wiley +1 more source
A note on the Taylor series expansions for multivariate characteristics of classical risk processes. [PDF]
The series expansion introduced by Frey and Schmidt (1996) [Taylor Series expansion for multivariate characteristics of classical risk processes.
Usábel, Miguel A.
core
Consensus Formation and Change are Enhanced by Neutrality
Neutral agents are shown to enhance both the formation and overturning of consensus in collective decision‐making. A general mathematical model and experiments with locusts and humans reveal that neutrality enables robust consensus via simple interactions and accelerates consensus change by reducing effective population size.
Andrei Sontag +3 more
wiley +1 more source
Evaluating the Utilities of Foundation Models in Single‐Cell Data Analysis
This study delivers the first systematic, task‐level evaluation of single‐cell foundation models across eight core analytical tasks. By benchmarking 10 leading models with the scEval framework, it reveals where foundation models truly add value, where task‐specific methods still dominate, and provides concrete, reproducible guidelines to steer the next
Tianyu Liu +4 more
wiley +1 more source
Quality Matters - the Expulsion of Professors and Ph.D. Student Outcomes in Nazi Germany [PDF]
I investigate the effect of faculty quality on Ph.D. student outcomes. To address the endogeneity of faculty quality I use exogenous variation provided by the expulsion of mathematics professors in Nazi Germany.
Fabian Waldinger
core
How Quantum Computers Fail: Quantum Codes, Correlations in Physical Systems, and Noise Accumulation [PDF]
The feasibility of computationally superior quantum computers is one of the most exciting and clear-cut scientific questions of our time. The question touches on fundamental issues regarding probability, physics, and computability, as well as on exciting
Kalai, Gil
core
Causal Prediction of TP53 Variant Pathogenicity Using a Perturbation‐Informed Protein Language Model
A TP53‐specific predictor, CaVepP53, is developed by fine‐tuning ESMC on experimentally validated variants, quantifying pathogenicity via Euclidean distances. It outperforms general‐purpose models and extends to five cancer genes, enabling interpretable variant classification for precision medicine.
Huiying Chen +15 more
wiley +1 more source
Geometry and connectivity are complementary structures, which have demonstrated their ability to represent the brain's functional activity. This study evaluates geometric and connectome eigenmodes as biologically informed constraints for EEG source localization.
Pok Him Siu +6 more
wiley +1 more source
This study presents a transferable modeling framework for carbon capture using aluminosilicates, integrating Universal Isotherm Modeling with experimental data. It reveals how ultramicropores, alumina content, and amine functionalization influence CO2 adsorption energetics.
Pooja Anil Kumar Nair +4 more
wiley +1 more source
Introduction to Mathematical Probability. [PDF]
J. A. Greenwood, J. V. Uspensky
+4 more sources

