Zobrazeno 1 - 10
of 16 201
pro vyhledávání: '"Mahan, A."'
Autor:
Basu, Riddhipratim, Mj, Mahan
We continue the study of the geometry of infinite geodesics in first passage percolation (FPP) on Gromov-hyperbolic groups G, initiated by Benjamini-Tessera and developed further by the authors. It was shown earlier by the authors that, given any fix
Externí odkaz:
http://arxiv.org/abs/2412.03067
Autor:
Havrilla, Alex, Dai, Andrew, O'Mahony, Laura, Oostermeijer, Koen, Zisler, Vera, Albalak, Alon, Milo, Fabrizio, Raparthy, Sharath Chandra, Gandhi, Kanishk, Abbasi, Baber, Phung, Duy, Iyer, Maia, Mahan, Dakota, Blagden, Chase, Gureja, Srishti, Hamdy, Mohammed, Li, Wen-Ding, Paolini, Giovanni, Ammanamanchi, Pawan Sasanka, Meyerson, Elliot
Synthetic data generation with Large Language Models is a promising paradigm for augmenting natural data over a nearly infinite range of tasks. Given this variety, direct comparisons among synthetic data generation algorithms are scarce, making it di
Externí odkaz:
http://arxiv.org/abs/2412.02980
Motivated by Gromov's geodesic flow problem on hyperbolic groups $G$, we develop in this paper an analog using random walks. This leads to a notion of a harmonic analog $\Theta$ of the Bowen-Margulis-Sullivan measure on $\partial^2 G$. We provide thr
Externí odkaz:
http://arxiv.org/abs/2411.14350
Artificial Intelligence (AI) techniques, especially Large Language Models (LLMs), have started gaining popularity among researchers and software developers for generating source code. However, LLMs have been shown to generate code with quality issues
Externí odkaz:
http://arxiv.org/abs/2411.04299
Autor:
Mohseni, Mahan, Cunha, Iann, Miravet, Daniel, Rodrigues, Alina Wania, Allami, Hassan, Assi, Ibsal, Korkusinski, Marek, Hawrylak, Pawel
This work presents steps toward the design of Majorana zero modes (MZM) in InAsP quantum dots (QD) embedded in an InP semiconducting nanowire in contact with a p-type superconductor described by the Kitaev Hamiltonian. The single particle spectrum is
Externí odkaz:
http://arxiv.org/abs/2410.22431
Autor:
Elmoznino, Eric, Marty, Tom, Kasetty, Tejas, Gagnon, Leo, Mittal, Sarthak, Fathi, Mahan, Sridhar, Dhanya, Lajoie, Guillaume
A central goal of machine learning is generalization. While the No Free Lunch Theorem states that we cannot obtain theoretical guarantees for generalization without further assumptions, in practice we observe that simple models which explain the trai
Externí odkaz:
http://arxiv.org/abs/2410.14086
Autor:
Mahan, Dakota, Van Phung, Duy, Rafailov, Rafael, Blagden, Chase, Lile, Nathan, Castricato, Louis, Fränken, Jan-Philipp, Finn, Chelsea, Albalak, Alon
Reinforcement Learning from Human Feedback (RLHF) has greatly improved the performance of modern Large Language Models (LLMs). The RLHF process is resource-intensive and technically challenging, generally requiring a large collection of human prefere
Externí odkaz:
http://arxiv.org/abs/2410.12832
Autor:
Mj, Mahan, Mukherjee, Sabyasachi
We prove a generalization of the Bers' simultaneous uniformization theorem in the world of algebraic correspondences. More precisely, we construct algebraic correspondences that simultaneously uniformize a pair of non-homeomorphic genus zero orbifold
Externí odkaz:
http://arxiv.org/abs/2409.10468
Autor:
Bernárdez, Guillermo, Telyatnikov, Lev, Montagna, Marco, Baccini, Federica, Papillon, Mathilde, Ferriol-Galmés, Miquel, Hajij, Mustafa, Papamarkou, Theodore, Bucarelli, Maria Sofia, Zaghen, Olga, Mathe, Johan, Myers, Audun, Mahan, Scott, Lillemark, Hansen, Vadgama, Sharvaree, Bekkers, Erik, Doster, Tim, Emerson, Tegan, Kvinge, Henry, Agate, Katrina, Ahmed, Nesreen K, Bai, Pengfei, Banf, Michael, Battiloro, Claudio, Beketov, Maxim, Bogdan, Paul, Carrasco, Martin, Cavallo, Andrea, Choi, Yun Young, Dasoulas, George, Elphick, Matouš, Escalona, Giordan, Filipiak, Dominik, Fritze, Halley, Gebhart, Thomas, Gil-Sorribes, Manel, Goomanee, Salvish, Guallar, Victor, Imasheva, Liliya, Irimia, Andrei, Jin, Hongwei, Johnson, Graham, Kanakaris, Nikos, Koloski, Boshko, Kovač, Veljko, Lecha, Manuel, Lee, Minho, Leroy, Pierrick, Long, Theodore, Magai, German, Martinez, Alvaro, Masden, Marissa, Mežnar, Sebastian, Miquel-Oliver, Bertran, Molina, Alexis, Nikitin, Alexander, Nurisso, Marco, Piekenbrock, Matt, Qin, Yu, Rygiel, Patryk, Salatiello, Alessandro, Schattauer, Max, Snopov, Pavel, Suk, Julian, Sánchez, Valentina, Tec, Mauricio, Vaccarino, Francesco, Verhellen, Jonas, Wantiez, Frederic, Weers, Alexander, Zajec, Patrik, Škrlj, Blaž, Miolane, Nina
This paper describes the 2nd edition of the ICML Topological Deep Learning Challenge that was hosted within the ICML 2024 ELLIS Workshop on Geometry-grounded Representation Learning and Generative Modeling (GRaM). The challenge focused on the problem
Externí odkaz:
http://arxiv.org/abs/2409.05211
In this note we study a family of graphs of groups over arbitrary base graphs where all vertex groups are isomorphic to a fixed countable sofic group $G$, and all edge groups $H
Externí odkaz:
http://arxiv.org/abs/2408.11724