Zobrazeno 1 - 10
of 138 311
pro vyhledávání: '"SMITH, A T"'
Autor:
Schuette, Cody R.
Publikováno v:
Army History, 2023 Jan 01(126), 57-58.
Externí odkaz:
https://www.jstor.org/stable/48725109
Efficient state space models (SSMs), such as linear recurrent neural networks and linear attention variants, offer computational advantages over Transformers but struggle with tasks requiring long-range in-context retrieval-like text copying, associa
Externí odkaz:
http://arxiv.org/abs/2411.01030
We perform the first global QCD analysis of electron-nucleon deep-inelastic scattering and related high-energy data including the beyond the Standard Model $U(1)_{B-L}$ gauge boson, $Z'$. Contrary to the dark photon case, we find no improvement in th
Externí odkaz:
http://arxiv.org/abs/2410.01205
Autor:
Gorsak, Cameron A., Bowman, Henry J., Gann, Katie R., Buontempo, Joshua T., Smith, Kathleen T., Tripathi, Pushpanshu, Steele, Jacob, Jena, Debdeep, Schlom, Darrell G., Xing, Huili Grace, Thompson, Michael O., Nair, Hari P.
In this study, we investigate in situ etching of \b{eta}-Ga2O3 in a metal-organic chemical vapor deposition (MOCVD) system using tert-Butyl chloride (TBCl). We report the successful etching of both heteroepitaxial (-201)-oriented and homoepitaxial (0
Externí odkaz:
http://arxiv.org/abs/2408.01574
Conventional nonlinear RNNs are not naturally parallelizable across the sequence length, unlike transformers and linear RNNs. Lim et. al. (2024) therefore tackle parallelized evaluation of nonlinear RNNs, posing it as a fixed point problem solved wit
Externí odkaz:
http://arxiv.org/abs/2407.19115
State space models (SSMs) have shown remarkable empirical performance on many long sequence modeling tasks, but a theoretical understanding of these models is still lacking. In this work, we study the learning dynamics of linear SSMs to understand ho
Externí odkaz:
http://arxiv.org/abs/2407.07279
Autor:
Mémoli, Facundo, Smith, Zane T.
This writeup describes ongoing work on designing and testing a certain family of correspondences between compact metric spaces that we call \emph{embedding-projection correspondences} (EPCs). Of particular interest are EPCs between spheres of differe
Externí odkaz:
http://arxiv.org/abs/2407.03295
Autor:
Parnichkun, Rom N., Massaroli, Stefano, Moro, Alessandro, Smith, Jimmy T. H., Hasani, Ramin, Lechner, Mathias, An, Qi, Ré, Christopher, Asama, Hajime, Ermon, Stefano, Suzuki, Taiji, Yamashita, Atsushi, Poli, Michael
We approach designing a state-space model for deep learning applications through its dual representation, the transfer function, and uncover a highly efficient sequence parallel inference algorithm that is state-free: unlike other proposed algorithms
Externí odkaz:
http://arxiv.org/abs/2405.06147
Autor:
Donnellan, James M. S., Oliver, Seb J., Bethermin, Matthieu, Bing, Longji, Bolatto, Alberto, Bradford, Charles M., Burgarella, Denis, Ciesla, Laure, Glenn, Jason, Pope, Alexandra, Serjeant, Stephen, Shirley, Raphael, Smith, JD T., Sorrell, Chris
The PRobe far-Infrared Mission for Astrophysics (PRIMA) concept aims to perform mapping with spectral coverage and sensitivities inaccessible to previous FIR space telescopes. PRIMA's imaging instrument, PRIMAger, provides unique hyperspectral imagin
Externí odkaz:
http://arxiv.org/abs/2404.06935
Autor:
Cuddy, Zachary
Publikováno v:
The History Teacher, 2019 Aug 01. 52(4), 725-727.
Externí odkaz:
https://www.jstor.org/stable/26823706