Zobrazeno 1 - 10
of 2 429
pro vyhledávání: '"A. Dimakis"'
Autor:
Matone, Marco, Dimakis, Nikolaos
In this work, we demonstrate that the recently introduced linear form of the Friedmann equations corresponds to the first-order WKB expansion of a quantum cosmological equation, indicating that both General Relativity (GR) contains aspects of Quantum
Externí odkaz:
http://arxiv.org/abs/2411.07961
Autor:
Daras, Giannis, Nie, Weili, Kreis, Karsten, Dimakis, Alex, Mardani, Morteza, Kovachki, Nikola Borislavov, Vahdat, Arash
Using image models naively for solving inverse video problems often suffers from flickering, texture-sticking, and temporal inconsistency in generated videos. To tackle these problems, in this paper, we view frames as continuous functions in the 2D s
Externí odkaz:
http://arxiv.org/abs/2410.16152
Autor:
Dimakis, Panagiotis, Rochon, Frédéric
Using an approach developed by Melrose to study the geometry at infinity of the Nakajima metric on the reduced Hilbert scheme of points on $\mathbb{C}^2$, we show that the Nakajima metric on a quiver variety is quasi-asymptotically conical (QAC) when
Externí odkaz:
http://arxiv.org/abs/2410.15424
Autor:
Dimakis, Panagiotis, Schulz, Sebastian
On a compact Riemann surface $\Sigma$ of genus $g>1$, equipped with a complex vector bundle $E$ of rank $2$ and degree zero let $M_H$ be the moduli space of Higgs bundles. $M_H$ admits a $\mathbb C^{\star}$-action and to each stable $\mathbb C^{\star
Externí odkaz:
http://arxiv.org/abs/2410.12945
We solve the gravitational field equations for a static, spherically symmetric spacetime within the framework of the symmetric teleparallel theory of gravity. Specifically, we derive new solutions within the context of power-law $f(Q)$ gravity and th
Externí odkaz:
http://arxiv.org/abs/2410.04513
Autor:
Daras, Giannis, Chung, Hyungjin, Lai, Chieh-Hsin, Mitsufuji, Yuki, Ye, Jong Chul, Milanfar, Peyman, Dimakis, Alexandros G., Delbracio, Mauricio
Diffusion models have become increasingly popular for generative modeling due to their ability to generate high-quality samples. This has unlocked exciting new possibilities for solving inverse problems, especially in image restoration and reconstruc
Externí odkaz:
http://arxiv.org/abs/2410.00083
Clinical diagnosis of stuttering requires an assessment by a licensed speech-language pathologist. However, this process is time-consuming and requires clinicians with training and experience in stuttering and fluency disorders. Unfortunately, only a
Externí odkaz:
http://arxiv.org/abs/2409.10704
Motivated by the rapid development of autonomous vehicle technology, this work focuses on the challenges of introducing them in ride-hailing platforms with conventional strategic human drivers. We consider a ride-hailing platform that operates a mixe
Externí odkaz:
http://arxiv.org/abs/2406.19014
Autor:
Li, Jeffrey, Fang, Alex, Smyrnis, Georgios, Ivgi, Maor, Jordan, Matt, Gadre, Samir, Bansal, Hritik, Guha, Etash, Keh, Sedrick, Arora, Kushal, Garg, Saurabh, Xin, Rui, Muennighoff, Niklas, Heckel, Reinhard, Mercat, Jean, Chen, Mayee, Gururangan, Suchin, Wortsman, Mitchell, Albalak, Alon, Bitton, Yonatan, Nezhurina, Marianna, Abbas, Amro, Hsieh, Cheng-Yu, Ghosh, Dhruba, Gardner, Josh, Kilian, Maciej, Zhang, Hanlin, Shao, Rulin, Pratt, Sarah, Sanyal, Sunny, Ilharco, Gabriel, Daras, Giannis, Marathe, Kalyani, Gokaslan, Aaron, Zhang, Jieyu, Chandu, Khyathi, Nguyen, Thao, Vasiljevic, Igor, Kakade, Sham, Song, Shuran, Sanghavi, Sujay, Faghri, Fartash, Oh, Sewoong, Zettlemoyer, Luke, Lo, Kyle, El-Nouby, Alaaeldin, Pouransari, Hadi, Toshev, Alexander, Wang, Stephanie, Groeneveld, Dirk, Soldaini, Luca, Koh, Pang Wei, Jitsev, Jenia, Kollar, Thomas, Dimakis, Alexandros G., Carmon, Yair, Dave, Achal, Schmidt, Ludwig, Shankar, Vaishaal
We introduce DataComp for Language Models (DCLM), a testbed for controlled dataset experiments with the goal of improving language models. As part of DCLM, we provide a standardized corpus of 240T tokens extracted from Common Crawl, effective pretrai
Externí odkaz:
http://arxiv.org/abs/2406.11794
Autor:
Lingam, Vijay, Tejaswi, Atula, Vavre, Aditya, Shetty, Aneesh, Gudur, Gautham Krishna, Ghosh, Joydeep, Dimakis, Alex, Choi, Eunsol, Bojchevski, Aleksandar, Sanghavi, Sujay
Popular parameter-efficient fine-tuning (PEFT) methods, such as LoRA and its variants, freeze pre-trained model weights \(W\) and inject learnable matrices \(\Delta W\). These \(\Delta W\) matrices are structured for efficient parameterization, often
Externí odkaz:
http://arxiv.org/abs/2405.19597