Zobrazeno 1 - 10
of 442 825
pro vyhledávání: '"Dean, A."'
In 2020, we introduced a deep reinforcement learning method capable of generating superhuman chip layouts, which we then published in Nature and open-sourced on GitHub. AlphaChip has inspired an explosion of work on AI for chip design, and has been d
Externí odkaz:
http://arxiv.org/abs/2411.10053
Autor:
Doron, Dean, Ribeiro, João
(abstract shortened due to space constraints) Existing constructions of seeded extractors with short seed length and large output length run in time $\Omega(n \log(1/\varepsilon))$ and often slower, where $n$ is the input source length and $\varepsil
Externí odkaz:
http://arxiv.org/abs/2411.07473
Autor:
Yi, Weixi, Wang, Yipei, Thorley, Natasha, Ng, Alexander, Punwani, Shonit, Kasivisvanathan, Veeru, Barratt, Dean C., Saeed, Shaheer Ullah, Hu, Yipeng
Current imaging-based prostate cancer diagnosis requires both MR T2-weighted (T2w) and diffusion-weighted imaging (DWI) sequences, with additional sequences for potentially greater accuracy improvement. However, measuring diffusion patterns in DWI se
Externí odkaz:
http://arxiv.org/abs/2411.07416
Autor:
Kopitar, Leon, Plohl, Nejc, Verboten, Mojca Tancer, Štiglic, Gregor, Watson, Roger, Korošak, Dean
The current system of scholarly publishing is often criticized for being slow, expensive, and not transparent. The rise of open access publishing as part of open science tenets, promoting transparency and collaboration, together with calls for resear
Externí odkaz:
http://arxiv.org/abs/2411.06282
Autor:
Martinien, Laurine, Ménard, François, Duchêne, Gaspard, Tazaki, Ryo, Perrin, Marshall D., Stapelfeldt, Karl R., Pinte, Christophe, Wolff, Schuyler G., Grady, Carol, Dominik, Carsten, Roumesy, Maxime, Ma, Jie, Ginski, Christian, Hines, Dean C., Schneider, Glenn
PDS 453 is a rare highly inclined disk where the stellar photosphere is seen at grazing incidence on the disk surface. Our goal is take advantage of this geometry to constrain the structure and composition of this disk, in particular the fact that it
Externí odkaz:
http://arxiv.org/abs/2411.04741
Autor:
Foster, Dean P., Hart, Sergiu
We provide bounds on the tail probabilities for simple procedures that generate random samples _without replacement_, when the probabilities of being selected need not be equal.
Externí odkaz:
http://arxiv.org/abs/2411.03955
Autor:
Wang, Zixuan, Mahar, Suyash, Li, Luyi, Park, Jangseon, Kim, Jinpyo, Michailidis, Theodore, Pan, Yue, Rosing, Tajana, Tullsen, Dean, Swanson, Steven, Ryoo, Kyung Chang, Park, Sungjoo, Zhao, Jishen
We present a thorough analysis of the use of CXL-based heterogeneous systems. We built a cluster of server systems that combines different vendor's CPUs and various types of CXL devices. We further developed a heterogeneous memory benchmark suite, He
Externí odkaz:
http://arxiv.org/abs/2411.02814
Autor:
Kenyon-Dean, Kian, Wang, Zitong Jerry, Urbanik, John, Donhauser, Konstantin, Hartford, Jason, Saberian, Saber, Sahin, Nil, Bendidi, Ihab, Celik, Safiye, Fay, Marta, Vera, Juan Sebastian Rodriguez, Haque, Imran S, Kraus, Oren
Large-scale cell microscopy screens are used in drug discovery and molecular biology research to study the effects of millions of chemical and genetic perturbations on cells. To use these images in downstream analysis, we need models that can map eac
Externí odkaz:
http://arxiv.org/abs/2411.02572
Autor:
Yin, Shi, Tan, Hongqi, Chong, Li Ming, Liu, Haofeng, Liu, Hui, Lee, Kang Hao, Tuan, Jeffrey Kit Loong, Ho, Dean, Jin, Yueming
Background: Cone-beam computed tomography (CBCT) plays a crucial role in image-guided radiotherapy, but artifacts and noise make them unsuitable for accurate dose calculation. Artificial intelligence methods have shown promise in enhancing CBCT quali
Externí odkaz:
http://arxiv.org/abs/2411.01575
Autor:
Bazavov, Alexei, Henke, Brandon, Hostetler, Leon, Lee, Dean, Lin, Huey-Wen, Pederiva, Giovanni, Shindler, Andrea
We present a comparison of different quantum state preparation algorithms and their overall efficiency for the Schwinger model with a theta term. While adiabatic state preparation (ASP) is proved to be effective, in practice it leads to large CNOT ga
Externí odkaz:
http://arxiv.org/abs/2411.00243