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Language models are increasingly capable and are being rapidly deployed on a population-level scale. As a result, the safety of these models is increasingly high-stakes. Fortunately, advances in alignment have significantly reduced the…

Machine Learning · Computer Science 2026-04-27 Rico Angell , Raghav Singhal , Zachary Horvitz , Zhou Yu , Rajesh Ranganath , Kathleen McKeown , He He

Causal discovery in multivariate extremes is challenging because extreme observations are sparse, dependent, and often affected by latent common shocks. Existing approaches focus on undirected extremal dependence, require prior graph…

Methodology · Statistics 2026-04-24 Mengran Li , Daniela Castro-Camilo

Distributions exhibiting fat tails occur frequently in many different areas of science. A dynamical reason for fat tails can be a so-called superstatistics, where one has a superposition of local Gaussians whose variance fluctuates on a…

Statistical Mechanics · Physics 2009-11-11 Christian Beck

Proliferating cell populations at steady state growth often exhibit broad protein distributions with exponential tails. The sources of this variation and its universality are of much theoretical interest. Here we address the problem by…

Populations and Evolution · Quantitative Biology 2008-07-24 Tamar Friedlander , Naama Brenner

Different questions related with analysis of extreme values and outliers arise frequently in practice. To exclude extremal observations and outliers is not a good decision because they contain important information about the observed…

Methodology · Statistics 2018-01-17 Pavlina K. Jordanova , Monika P. Petkova

We establish exponential inequalities and Cramer-type moderate deviation theorems for a class of V-statistics under strong mixing conditions. Our theory is developed via kernel expansion based on random Fourier features. This type of…

Statistics Theory · Mathematics 2019-02-08 Yandi Shen , Fang Han , Daniela Witten

We characterize the distributions of size and duration of avalanches propagating in complex networks. By an avalanche we mean the sequence of events initiated by the externally stimulated `excitation' of a network node, which may, with some…

Disordered Systems and Neural Networks · Physics 2013-10-22 Daniel B. Larremore , Marshall Y. Carpenter , Edward Ott , Juan G. Restrepo

Based on a multisector general equilibrium framework, we show that the sectoral elasticity of substitution plays the key role in the evolution of asymmetric tails of macroeconomic fluctuations and the establishment of robustness against…

General Economics · Economics 2024-12-31 Satoshi Nakano , Kazuhiko Nishimura

We investigate front propagation in systems with diffusive and sub-diffusive behavior. The scaling behavior of moments of the diffusive problem, both in the standard and in the anomalous cases, is not enough to determine the features of the…

Statistical Mechanics · Physics 2016-09-06 Maurizio Serva , Davide Vergni , Angelo Vulpiani

Using the optimal velocity (OV) model as an example, we show that in the non-linear regime there is an emergent quantity that gives the extremum headways in the cluster formation, as well as the coexistence curve separating the absolute…

Statistical Mechanics · Physics 2016-05-11 Bo Yang , Xihua Xu , John Z. F. Pang , Christopher Monterola

The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behavior into a central question of modern science. Current models of human dynamics,…

Statistical Mechanics · Physics 2009-11-11 Albert-László Barabási

We propose new analytical tools for describing growth-rate distributions generated by stationary time-series. Our analysis shows how deviations from normality are not pathological behaviour, as suggested by some traditional views, but…

Data Analysis, Statistics and Probability · Physics 2026-04-01 Edgardo Brigatti

The block maxima method is one of the most popular approaches for extreme value analysis with independent and identically distributed observations in the domain of attraction of an extreme value distribution. The lack of a rigorous study on…

Methodology · Statistics 2022-04-12 Simone A Padoan , Stefano Rizzelli

The ETAS model is widely employed to model the spatio-temporal distribution of earthquakes, generally using spatially invariant parameters. We propose an efficient method for the estimation of spatially varying parameters, using the…

Geophysics · Physics 2017-06-28 Shyam Nandan , Guy Ouillon , Stefan Wiemer , Didier Sornette

The Peaks Over Threshold (POT) method is the most popular statistical method for the analysis of univariate extremes. Even though there is a rich applied literature on Bayesian inference for the POT, the asymptotic theory for such proposals…

Statistics Theory · Mathematics 2025-04-01 Clément Dombry , Simone A. Padoan , Stefano Rizzelli

Following Hergarten and Neugebauer [2002] who discovered aftershock and foreshock sequences in the Olami-Feder-Christensen (OFC) discrete block-spring earthquake model, we investigate to what degree the simple toppling mechanism of this…

Condensed Matter · Physics 2009-11-10 A. Helmstetter , S. Hergarten , D. Sornette

Identifying the generating mechanism of a network is challenging as, more often than not, only snapshots are available, but not the full evolution. One candidate for the generating mechanism is preferential attachment which, in its simplest…

Methodology · Statistics 2025-10-07 Thomas Boughen , Clement Lee , Vianey Palacios Ramirez

We propose a mean functional which exists for any probability distributions, and which characterizes the Pareto distribution within the set of distributions with finite left endpoint. This is in sharp contrast to the mean excess plot which…

Methodology · Statistics 2024-04-05 Bernhard Klar

Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes. We provide direct evidence that for five human…

Physics and Society · Physics 2009-11-11 A. Vazquez , J. Gama Oliveira , Z. Dezso , K. -I. Goh , I. Kondor , A. -L. Barabasi

Out-of-distribution (OOD) generalization is a complicated problem due to the idiosyncrasies of possible distribution shifts between training and test domains. Most benchmarks employ diverse datasets to address this issue; however, the…

Machine Learning · Computer Science 2023-12-18 Kaican Li , Yifan Zhang , Lanqing Hong , Zhenguo Li , Nevin L. Zhang