Zobrazeno 1 - 10
of 59 913
pro vyhledávání: '"Kirsch, A."'
A De Bruijn cycle is a cyclic sequence in which every word of length $n$ over an alphabet $\mathcal{A}$ appears exactly once. De Bruijn tori are a two-dimensional analogue. Motivated by recent progress on universal partial cycles and words, which sho
Externí odkaz:
http://arxiv.org/abs/2409.12417
Autor:
Kirsch, Andreas
Epistemic uncertainty is crucial for safety-critical applications and out-of-distribution detection tasks. Yet, we uncover a paradoxical phenomenon in deep learning models: an epistemic uncertainty collapse as model complexity increases, challenging
Externí odkaz:
http://arxiv.org/abs/2409.02628
Large Language Models (LLMs) generate longform text by successively sampling the next token based on the probability distribution of the token vocabulary at each decoding step. Current popular truncation sampling methods such as top-$p$ sampling, als
Externí odkaz:
http://arxiv.org/abs/2407.01082
Autor:
Park, Jihun, Horn, Jarryd A., Kirsch, Dylan J., Pant, Rohit K., Yoon, Hyeok, Baek, Sungha, Sarker, Suchismita, Mehta, Apurva, Zhang, Xiaohang, Lee, Seunghun, Greene, Richard, Paglione, Johnpierre, Takeuchi, Ichiro
The Bi${-}$Ni binary system has been of interest due to possible unconventional superconductivity aroused therein, such as time-reversal symmetry breaking in Bi/Ni bilayers or the coexistence of superconductivity and ferromagnetism in Bi$_3$Ni crysta
Externí odkaz:
http://arxiv.org/abs/2406.18704
Recently, transductive learning methods, which leverage holdout sets during training, have gained popularity for their potential to improve speed, accuracy, and fairness in machine learning models. Despite this, the composition of the holdout set its
Externí odkaz:
http://arxiv.org/abs/2406.12011
Autor:
Brandfonbrener, David, Zhang, Hanlin, Kirsch, Andreas, Schwarz, Jonathan Richard, Kakade, Sham
Selecting high-quality data for pre-training is crucial in shaping the downstream task performance of language models. A major challenge lies in identifying this optimal subset, a problem generally considered intractable, thus necessitating scalable
Externí odkaz:
http://arxiv.org/abs/2406.10670
We provide a mathematical analysis of the Dynamical Mean-Field Theory, a celebrated representative of a class of approximations in quantum mechanics known as embedding methods. We start by a pedagogical and self-contained mathematical formulation of
Externí odkaz:
http://arxiv.org/abs/2406.03384
Temporal credit assignment in reinforcement learning is challenging due to delayed and stochastic outcomes. Monte Carlo targets can bridge long delays between action and consequence but lead to high-variance targets due to stochasticity. Temporal dif
Externí odkaz:
http://arxiv.org/abs/2405.03878
Autor:
Koraltan, Sabri, Gupta, Rahul, Pradeep, Reshma Peremadathil, Kammerbauer, Fabian, Kononenko, Iryna, Prügl, Klemens, Kirsch, Michael, Aichner, Bernd, Helbig, Santiago, Bruckner, Florian, Abert, Claas, Mandru, Andrada Oana, Satz, Armin, Jakob, Gerhard, Hug, Hans Josef, Kläui, Mathias, Suess, Dieter
Magnetic skyrmions are topologically protected local magnetic solitons that are promising for storage, logic or general computing applications. In this work, we demonstrate that we can use a skyrmion device based on [W/CoFeB/MgO] 1 0 multilayers for
Externí odkaz:
http://arxiv.org/abs/2403.16725
Autor:
Hu, Guanghui, Kirsch, Andreas
This is a continuation of the authors' previous work (A. Kirsch, Math. Meth. Appl. Sci., 45 (2022): 5737-5773.) on well-posedness of time-harmonic scattering by locally perturbed periodic curves of Dirichlet kind. The scattering interface is supposed
Externí odkaz:
http://arxiv.org/abs/2403.07340