Zobrazeno 1 - 10
of 69 965
pro vyhledávání: '"A Shyam"'
Autor:
Gairola, Shashank, Subramanian, Smitha, M., Sreedevi, Menon, Shyam H, Mondal, Chayan, Krishna, Sriram, Das, Mousumi, Subramaniam, Annapurni
Molecular clouds fragment under the action of supersonic turbulence & gravity which results in a scale-free hierarchical distribution of star formation (SF) within galaxies. Recent studies suggest that the hierarchical distribution of SF in nearby ga
Externí odkaz:
http://arxiv.org/abs/2412.00872
In the trace reconstruction problem our goal is to learn an unknown string $x\in \{0,1\}^n$ given independent traces of $x$. A trace is obtained by independently deleting each bit of $x$ with some probability $\delta$ and concatenating the remaining
Externí odkaz:
http://arxiv.org/abs/2411.18765
Autor:
Kumar, Shyam, Hong, Jiarong
Despite its potential for label-free particle diagnostics, holographic microscopy is limited by specialized processing methods that struggle to generalize across diverse settings. We introduce a deep learning architecture leveraging human perception
Externí odkaz:
http://arxiv.org/abs/2411.16439
Autor:
Glorioso, Paolo, Anthony, Quentin, Tokpanov, Yury, Golubeva, Anna, Shyam, Vasudev, Whittington, James, Pilault, Jonathan, Millidge, Beren
In this technical report, we present the Zamba2 series -- a suite of 1.2B, 2.7B, and 7.4B parameter hybrid Mamba2-transformer models that achieve state of the art performance against the leading open-weights models of their class, while achieving sub
Externí odkaz:
http://arxiv.org/abs/2411.15242
In this paper we extend the theory of energy solutions for singular SPDEs, focusing on equations driven by highly irregular noise with bilinear nonlinearities, including scaling critical examples. By introducing Gelfand triples and leveraging infinit
Externí odkaz:
http://arxiv.org/abs/2411.07680
Autor:
Dai, Wei, Liu, Gangqiang, Joshi, Vidul, Miano, Alessandro, Sivak, Volodymyr, Shankar, Shyam, Devoret, Michel H.
Josephson element-based parametric amplifiers (JPAs) typically require rf pump power that is several orders of magnitude stronger than the maximum signal power they can handle. The low power efficiency and strong pump leakage towards signal circuitry
Externí odkaz:
http://arxiv.org/abs/2411.07208
We study the problem of learning mixtures of Gaussians with approximate differential privacy. We prove that roughly $kd^2 + k^{1.5} d^{1.75} + k^2 d$ samples suffice to learn a mixture of $k$ arbitrary $d$-dimensional Gaussians up to low total variat
Externí odkaz:
http://arxiv.org/abs/2411.02298
Autor:
Aamand, Anders, Andoni, Alexandr, Chen, Justin Y., Indyk, Piotr, Narayanan, Shyam, Silwal, Sandeep, Xu, Haike
We study the density estimation problem defined as follows: given $k$ distributions $p_1, \ldots, p_k$ over a discrete domain $[n]$, as well as a collection of samples chosen from a ``query'' distribution $q$ over $[n]$, output $p_i$ that is ``close'
Externí odkaz:
http://arxiv.org/abs/2410.23087
Autor:
Wang, Xinyu, Zhang, Wenbo, Koneru, Sai, Guo, Hangzhi, Mingole, Bonam, Sundar, S. Shyam, Rajtmajer, Sarah, Yadav, Amulya
With the rise of AI-generated content spewed at scale from large language models (LLMs), genuine concerns about the spread of fake news have intensified. The perceived ability of LLMs to produce convincing fake news at scale poses new challenges for
Externí odkaz:
http://arxiv.org/abs/2410.19250
This manuscript summarizes work on the Capsule Vision Challenge 2024 by MISAHUB. To address the multi-class disease classification task, which is challenging due to the complexity and imbalance in the Capsule Vision challenge dataset, this paper prop
Externí odkaz:
http://arxiv.org/abs/2410.17863