Zobrazeno 1 - 10
of 16 598
pro vyhledávání: '"Siddharth, P."'
Autor:
Yilmaz, Figen, Singh, Siddharth, Zwanenburg, Martijn F. S., Hu, Jinlun, Stefanski, Taryn V., Andersen, Christian Kraglund
Superconducting circuits are being employed for large-scale quantum devices, and a pertinent challenge is to perform accurate numerical simulations of device parameters. One of the most advanced methods for analyzing superconducting circuit designs i
Externí odkaz:
http://arxiv.org/abs/2411.15039
Auto-SPICE is the first fully automated framework leveraging large language models (LLMs) to generate Simulation Programs with Integrated Circuit Emphasis (SPICE) netlists. It addresses a long-standing challenge in automating netlist generation for a
Externí odkaz:
http://arxiv.org/abs/2411.14299
Training of large-scale text-to-image and image-to-image models requires a huge amount of annotated data. While text-to-image datasets are abundant, data available for instruction-based image-to-image tasks like object addition and removal is limited
Externí odkaz:
http://arxiv.org/abs/2411.13794
We investigate the concept of algorithmic replicability introduced by Impagliazzo et al. 2022, Ghazi et al. 2021, Ahn et al. 2024 in an online setting. In our model, the input sequence received by the online learner is generated from time-varying dis
Externí odkaz:
http://arxiv.org/abs/2411.13730
Autor:
Stefanski, Taryn V., Yilmaz, Figen, Huang, Eugene Y., Zwanenburg, Martijn F. S., Singh, Siddharth, Wang, Siyu, Splitthoff, Lukas J., Andersen, Christian Kraglund
The ability to perform rapid, high fidelity readout of a qubit state is an important requirement for quantum algorithms and, in particular, for enabling operations such as mid-circuit measurements and measurement-based feedback for error correction s
Externí odkaz:
http://arxiv.org/abs/2411.13437
Autor:
Abel, Elliott, Crevasse, Peyton, Grinspan, Yvan, Mazioud, Selma, Ogundipe, Folu, Reimann, Kristof, Schueler, Ellie, Steindl, Andrew J., Zhang, Ellen, Bhaskar, Dhananjay, Viswanath, Siddharth, Zhang, Yanlei, Rudner, Tim G. J., Adelstein, Ian, Krishnaswamy, Smita
Drawing motivation from the manifold hypothesis, which posits that most high-dimensional data lies on or near low-dimensional manifolds, we apply manifold learning to the space of neural networks. We learn manifolds where datapoints are neural networ
Externí odkaz:
http://arxiv.org/abs/2411.12626
Autor:
Wyder, Philippe Martin, Bakhda, Riyaan, Zhao, Meiqi, Booth, Quinn A., Modi, Matthew E., Song, Andrew, Kang, Simon, Wu, Jiahao, Patel, Priya, Kasumi, Robert T., Yi, David, Garg, Nihar Niraj, Jhunjhunwala, Pranav, Bhutoria, Siddharth, Tong, Evan H., Hu, Yuhang, Goldfeder, Judah, Mustel, Omer, Kim, Donghan, Lipson, Hod
Biological lifeforms can heal, grow, adapt, and reproduce -- abilities essential for sustained survival and development. In contrast, robots today are primarily monolithic machines with limited ability to self-repair, physically develop, or incorpora
Externí odkaz:
http://arxiv.org/abs/2411.11192
Autor:
Zhu, Yinxuan, Allerman, Andrew A., Joishi, Chandan, Pratt, Jonathan, Xavier, Agnes Maneesha Dominic Merwin, Ortiz, Gabriel Calderon, Klein, Brianna A., Armstrong, Andrew, Hwang, Jinwoo, Rajan, Siddharth
We report on the heterostructure and interfacial engineering of metalorganic chemical vapor deposition (MOCVD) grown reverse-graded contacts to ultra-wide bandgap AlGaN. A record low contact resistivity of 1.4 x 10-6 Ohm.cm2 was reported on an Al0.82
Externí odkaz:
http://arxiv.org/abs/2411.10566
Autor:
Roheda, Siddharth
In recent years, image synthesis has achieved remarkable advancements, enabling diverse applications in content creation, virtual reality, and beyond. We introduce a novel approach to image generation using Auto-Regressive (AR) modeling, which levera
Externí odkaz:
http://arxiv.org/abs/2411.10180
Publikováno v:
17th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2024)
In today's Function-as-a-Service offerings, a programmer is usually responsible for configuring function memory for its successful execution, which allocates proportional function resources such as CPU and network. However, right-sizing the function
Externí odkaz:
http://arxiv.org/abs/2411.07444