English
Related papers

Related papers: Merging exchangeable occupancy models: $\mathcal{M…

200 papers

In this work we obtain mixing (and in some cases sharp mixing rates) for a reasonable large class of invertible systems preserving an infinite measure. The examples considered here are the invertible analogue of both Markov and non Markov…

Dynamical Systems · Mathematics 2014-11-24 Carlangelo Liverani , Dalia Terhesiu

Quantum gates that temporarily increase singlet-triplet splitting in order to swap electronic spins in coupled quantum dots, lead inevitably to a finite double-occupancy probability for both dots. By solving the time-dependent Schr\"odinger…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 John Schliemann , Daniel Loss , A. H. MacDonald

We describe an approach to improving model fitting and model generalization that considers the entropy of distributions of modelling residuals. We use simple simulations to demonstrate the observational signatures of overfitting on ordered…

Methodology · Statistics 2019-08-05 Barnaby Rowe

In this article the problem of reconstructing the pattern of connection between agents from partial empirical data in a macro-economic model is addressed, given a set of behavioral equations. This systemic point of view puts the focus on…

General Economics · Economics 2019-01-30 Aurélien Hazan

A critical decision point when training predictors using multiple studies is whether studies should be combined or treated separately. We compare two multi-study prediction approaches in the presence of potential heterogeneity in…

Machine Learning · Statistics 2024-12-13 Zoe Guan , Giovanni Parmigiani , Prasad Patil

Transformer models, which leverage architectural improvements like self-attention, perform remarkably well on Natural Language Processing (NLP) tasks. The self-attention mechanism is position agnostic. In order to capture positional…

Computation and Language · Computer Science 2021-09-28 Zhiheng Huang , Davis Liang , Peng Xu , Bing Xiang

Motivated by an ongoing project on computer aided derivation of asymptotic models governed by partial differential equations, we introduce a class of term transformations that consists of traversal strategies and insertion of contexts. We…

Logic in Computer Science · Computer Science 2021-12-15 Walid Belkhir , Nicolas Ratier , Duy Duc Nguyen , Michel Lenczner

The Jaynes-Cummings model is the simplest fully quantum model that describes the interaction between light and matter. We extend a previous analysis by Phoenix and Knight (S. J. D. Phoenix, P. L. Knight, Annals of Physics 186, 381). of the…

Quantum Physics · Physics 2009-11-11 E. Boukobza , D. J. Tannor

Recent advancements in building domain-specific large language models (LLMs) have shown remarkable success, especially in tasks requiring reasoning abilities like logical inference over complex relationships and multi-step problem solving.…

We introduce a minimal model of multilevel selection on structured populations, considering the interplay between game theory and population dynamics. Through a bottleneck process, finite groups are formed with cooperators and defectors…

Populations and Evolution · Quantitative Biology 2023-10-02 Jeferson J. Arenzon , Luca Peliti

We develop operator renewal theory for flows and apply this to infinite ergodic theory. In particular we obtain results on mixing for a large class of infinite measure semiflows. Examples of systems covered by our results include…

Dynamical Systems · Mathematics 2014-04-11 Ian Melbourne , Dalia Terhesiu

Entanglement and information are powerful lenses to probe phases transitions in many-body systems. Motivated by recent cold atom experiments, which are now able to measure the corresponding information-theoretic quantities, we study the…

Strongly Correlated Electrons · Physics 2019-02-20 C. Walsh , P. Sémon , D. Poulin , G. Sordi , A. -M. S. Tremblay

Deep model fusion/merging is an emerging technique that merges the parameters or predictions of multiple deep learning models into a single one. It combines the abilities of different models to make up for the biases and errors of a single…

Machine Learning · Computer Science 2023-09-28 Weishi Li , Yong Peng , Miao Zhang , Liang Ding , Han Hu , Li Shen

Mixture of Experts (MoE) architectures have significantly increased computational efficiency in both research and real-world applications of large-scale machine learning models. However, their scalability and efficiency under memory…

There are many entities that disseminate in the physical space - information, gossip, mood, innovation etc. Personal spaces are also entities that disperse and interplay. In this work we study the emergence of configurations formed by…

Multiagent Systems · Computer Science 2024-05-31 Jaroslav Horáček , Miroslav Rada

The thermodynamic definition of entropy can be extended to nonequilibrium systems based on its relation to information. To apply this definition in practice requires access to the physical system's microstates, which may be prohibitively…

Statistical Mechanics · Physics 2020-08-21 Gil Ariel , Haim Diamant

In this paper we investigate mixing and transport in correspondence of a meandering jet. The large-scale flow field is a kinematically assigned streamfunction. Two basic mixing mechanisms are considered, first separately and then combined…

chao-dyn · Physics 2009-10-31 M. Cencini , G. Lacorata , A. Vulpiani , E. Zambianchi

Computer simulation of the hopping charge transport in disordered organic materials has been carried out explicitly taking into account charge-charge interactions. This approach provides a possibility to take into account dynamic…

Disordered Systems and Neural Networks · Physics 2015-05-13 Sergey V. Novikov

We present the effect of mergers in the dynamics of the three-agent model studied by Ben-Naim, Kahng and Kim and by Rador and Mungan. Mergers are possible in three-agent games because two agents can combine forces against the third player…

Physics and Society · Physics 2011-12-09 T. Rador , R. Derici

Model merging aims to efficiently combine the weights of multiple expert models, each trained on a specific task, into a single multi-task model, with strong performance across all tasks. When applied to all but the last layer of weights,…

Machine Learning · Computer Science 2024-10-17 Ekansh Sharma , Daniel M. Roy , Gintare Karolina Dziugaite