Zobrazeno 1 - 10
of 914
pro vyhledávání: '"Tolias, P P"'
Autor:
Dornheim, Tobias, Bonitz, Michael, Moldabekov, Zhandos, Schwalbe, Sebastian, Tolias, Panagiotis, Vorberger, Jan
We present extensive new \emph{ab initio} path integral Monte Carlo (PIMC) simulation results for the chemical potential of the warm dense uniform electron gas (UEG), spanning a broad range of densities and temperatures. This is achieved by following
Externí odkaz:
http://arxiv.org/abs/2412.15777
We explore the recently introduced $\eta$-ensemble approach to compute the free energy directly from \emph{ab initio} path integral Monte Carlo (PIMC) simulations [T.~Dornheim \emph{et al.}, arXiv:2407.01044] and apply it to the archetypal uniform el
Externí odkaz:
http://arxiv.org/abs/2412.13596
This paper addresses supervised deep metric learning for open-set image retrieval, focusing on three key aspects: the loss function, mixup regularization, and model initialization. In deep metric learning, optimizing the retrieval evaluation metric,
Externí odkaz:
http://arxiv.org/abs/2412.12432
Autor:
Efthymiadis, Nikos, Psomas, Bill, Laskar, Zakaria, Karantzalos, Konstantinos, Avrithis, Yannis, Chum, Ondřej, Tolias, Giorgos
This work addresses composed image retrieval in the context of domain conversion, where the content of a query image is retrieved in the domain specified by the query text. We show that a strong vision-language model provides sufficient descriptive p
Externí odkaz:
http://arxiv.org/abs/2412.03297
Autor:
Mineault, Patrick, Zanichelli, Niccolò, Peng, Joanne Zichen, Arkhipov, Anton, Bingham, Eli, Jara-Ettinger, Julian, Mackevicius, Emily, Marblestone, Adam, Mattar, Marcelo, Payne, Andrew, Sanborn, Sophia, Schroeder, Karen, Tavares, Zenna, Tolias, Andreas
As AI systems become increasingly powerful, the need for safe AI has become more pressing. Humans are an attractive model for AI safety: as the only known agents capable of general intelligence, they perform robustly even under conditions that deviat
Externí odkaz:
http://arxiv.org/abs/2411.18526
The recently derived Fourier--Matsubara expansion of imaginary--time correlation functions comprises an exact result of linear response theory for finite-temperature quantum many-body systems. In its density--density version, the expansion facilitate
Externí odkaz:
http://arxiv.org/abs/2411.04904
The density-density correlations of the non-interacting finite temperature electron gas are discussed in detail. Starting from the ideal linear density response function and utilizing general relations from linear response theory, known and novel exp
Externí odkaz:
http://arxiv.org/abs/2410.22942
Autor:
Vorberger, Jan, Dornheim, Tobias, Böhme, Maximilian P., Moldabekov, Zhandos, Tolias, Panagiotis
We derive equations of motion for higher order density response functions using the theory of thermodynamic Green's functions. We also derive expressions for the higher order generalized dielectric functions and polarization functions. Moreover, we r
Externí odkaz:
http://arxiv.org/abs/2410.01845
Single-source domain generalization attempts to learn a model on a source domain and deploy it to unseen target domains. Limiting access only to source domain data imposes two key challenges - how to train a model that can generalize and how to verif
Externí odkaz:
http://arxiv.org/abs/2409.19774
Autor:
Dornheim, Tobias, Bellenbaum, Hannah M., Bethkenhagen, Mandy, Hansen, Stephanie B., Böhme, Maximilian P., Döppner, Tilo, Fletcher, Luke B., Gawne, Thomas, Gericke, Dirk O., Hamel, Sebastien, Kraus, Dominik, MacDonald, Michael J., Moldabekov, Zhandos A., Preston, Thomas R., Redmer, Ronald, Schörner, Maximilian, Schwalbe, Sebastian, Tolias, Panagiotis, Vorberger, Jan
X-ray Thomson scattering (XRTS) has emerged as a powerful tool for the diagnostics of matter under extreme conditions. In principle, it gives one access to important system parameters such as the temperature, density, and ionization state, but the in
Externí odkaz:
http://arxiv.org/abs/2409.08591