Zobrazeno 1 - 10
of 33 817
pro vyhledávání: '"Julius, P."'
This paper addresses the question of whether or not uncoupled online learning algorithms converge to the Nash equilibrium in pricing competition or whether they can learn to collude. Algorithmic collusion has been debated among competition regulators
Externí odkaz:
http://arxiv.org/abs/2412.15707
Autor:
Frieder, Simon, Bayer, Jonas, Collins, Katherine M., Berner, Julius, Loader, Jacob, Juhász, András, Ruehle, Fabian, Welleck, Sean, Poesia, Gabriel, Griffiths, Ryan-Rhys, Weller, Adrian, Goyal, Anirudh, Lukasiewicz, Thomas, Gowers, Timothy
The suite of datasets commonly used to train and evaluate the mathematical capabilities of AI-based mathematical copilots (primarily large language models) exhibit several shortcomings. These limitations include a restricted scope of mathematical com
Externí odkaz:
http://arxiv.org/abs/2412.15184
Autor:
Busse, Julius
Motivated by a recent publication by Ishiwata and Nakata (2022), we prove that sufficiently regular stochastic delay differential equations (SDDEs) with a single discrete delay have blow up solutions if and only if their undelayed counterparts have t
Externí odkaz:
http://arxiv.org/abs/2412.13383
Autor:
de Payrebrune, Kristin M., Flaßkamp, Kathrin, Ströhla, Tom, Sattel, Thomas, Bestle, Dieter, Röder, Benedict, Eberhard, Peter, Peitz, Sebastian, Stoffel, Marcus, Rutwik, Gulakala, Aditya, Borse, Wohlleben, Meike, Sextro, Walter, Raff, Maximilian, Remy, C. David, Yadav, Manish, Stender, Merten, van Delden, Jan, Lüddecke, Timo, Langer, Sabine C., Schultz, Julius, Blech, Christopher
Artificial intelligence (AI) is driving transformative changes across numerous fields, revolutionizing conventional processes and creating new opportunities for innovation. The development of mechatronic systems is undergoing a similar transformation
Externí odkaz:
http://arxiv.org/abs/2412.12230
Autor:
Kossaifi, Jean, Kovachki, Nikola, Li, Zongyi, Pitt, David, Liu-Schiaffini, Miguel, George, Robert Joseph, Bonev, Boris, Azizzadenesheli, Kamyar, Berner, Julius, Anandkumar, Anima
We present NeuralOperator, an open-source Python library for operator learning. Neural operators generalize neural networks to maps between function spaces instead of finite-dimensional Euclidean spaces. They can be trained and inferenced on input an
Externí odkaz:
http://arxiv.org/abs/2412.10354
Non-Abelian gauge theories underlie our understanding of fundamental forces of modern physics. Simulating them on quantum hardware is an outstanding challenge in the rapidly evolving field of quantum simulation. A key prerequisite is the protection o
Externí odkaz:
http://arxiv.org/abs/2412.07844
Autor:
Cavaglià, Andrea, Gromov, Nikolay, Julius, Julius, Preti, Michelangelo, Sokolova, Nika Sergeevna
We continue our study of the defect CFT on a Maldacena-Wilson line in N=4 Super-Yang-Mills theory using Bootstrability -- the conformal bootstrap supplemented with exact integrability data. In this paper, we extend this program to charged sectors of
Externí odkaz:
http://arxiv.org/abs/2412.07624
Autor:
Chen, Junhua, Richter, Lorenz, Berner, Julius, Blessing, Denis, Neumann, Gerhard, Anandkumar, Anima
An effective approach for sampling from unnormalized densities is based on the idea of gradually transporting samples from an easy prior to the complicated target distribution. Two popular methods are (1) Sequential Monte Carlo (SMC), where the trans
Externí odkaz:
http://arxiv.org/abs/2412.07081
We discuss vertex patch smoothers as overlapping domain decomposition methods for fourth order elliptic partial differential equations. We show that they are numerically very efficient and yield high convergence rates. Furthermore, we discuss low ran
Externí odkaz:
http://arxiv.org/abs/2412.05082
Autor:
Dheeshjith, Surya, Subel, Adam, Adcroft, Alistair, Busecke, Julius, Fernandez-Granda, Carlos, Gupta, Shubham, Zanna, Laure
AI emulators for forecasting have emerged as powerful tools that can outperform conventional numerical predictions. The next frontier is to build emulators for long climate simulations with skill across a range of spatiotemporal scales, a particularl
Externí odkaz:
http://arxiv.org/abs/2412.03795