Zobrazeno 1 - 10
of 181 375
pro vyhledávání: '"SRINIVASAN, A."'
In this work, we propose a first-order sampling method called the Metropolis-adjusted Preconditioned Langevin Algorithm for approximate sampling from a target distribution whose support is a proper convex subset of $\mathbb{R}^{d}$. Our proposed meth
Externí odkaz:
http://arxiv.org/abs/2412.18701
Autor:
Zhao, Mingjun, Dickstein, Leah, Nadig, Akshay S., Zhou, Wenjun, Aparanji, Santosh, Estrada, Hector Garcia, Liu, Shing-Jiuan, Zhou, Ting, Yang, Weijian, Lord, Aaron, Srinivasan, Vivek J.
It has been shown that light speckle fluctuations provide a means for noninvasive measurements of cerebral blood flow index (CBFi). While conventional Diffuse Correlation Spectroscopy (DCS) provides marginal brain sensitivity for CBFi in adult humans
Externí odkaz:
http://arxiv.org/abs/2412.17724
Autor:
Alzayer, Hadi, Henzler, Philipp, Barron, Jonathan T., Huang, Jia-Bin, Srinivasan, Pratul P., Verbin, Dor
Reconstructing the geometry and appearance of objects from photographs taken in different environments is difficult as the illumination and therefore the object appearance vary across captured images. This is particularly challenging for more specula
Externí odkaz:
http://arxiv.org/abs/2412.15211
The Piping and Instrumentation Diagrams (P&IDs) are foundational to the design, construction, and operation of workflows in the engineering and process industries. However, their manual creation is often labor-intensive, error-prone, and lacks robust
Externí odkaz:
http://arxiv.org/abs/2412.12898
Given an edge-colored graph, the goal of the proportional fair matching problem is to find a maximum weight matching while ensuring proportional representation (with respect to the number of edges) of each color. The colors may correspond to demograp
Externí odkaz:
http://arxiv.org/abs/2412.11238
Autor:
Pagnoni, Artidoro, Pasunuru, Ram, Rodriguez, Pedro, Nguyen, John, Muller, Benjamin, Li, Margaret, Zhou, Chunting, Yu, Lili, Weston, Jason, Zettlemoyer, Luke, Ghosh, Gargi, Lewis, Mike, Holtzman, Ari, Iyer, Srinivasan
We introduce the Byte Latent Transformer (BLT), a new byte-level LLM architecture that, for the first time, matches tokenization-based LLM performance at scale with significant improvements in inference efficiency and robustness. BLT encodes bytes in
Externí odkaz:
http://arxiv.org/abs/2412.09871
Autor:
Joglekar, Advait, Umesh, Srinivasan
Neural Machine Translation (NMT) models are typically trained on datasets with limited exposure to Scientific, Technical and Educational domains. Translation models thus, in general, struggle with tasks that involve scientific understanding or techni
Externí odkaz:
http://arxiv.org/abs/2412.09025
Autor:
Trevithick, Alex, Paiss, Roni, Henzler, Philipp, Verbin, Dor, Wu, Rundi, Alzayer, Hadi, Gao, Ruiqi, Poole, Ben, Barron, Jonathan T., Holynski, Aleksander, Ramamoorthi, Ravi, Srinivasan, Pratul P.
Novel-view synthesis techniques achieve impressive results for static scenes but struggle when faced with the inconsistencies inherent to casual capture settings: varying illumination, scene motion, and other unintended effects that are difficult to
Externí odkaz:
http://arxiv.org/abs/2412.07696
Autor:
Zhang, Ruiqi, Motes, Brandon, Tan, Shaun, Lu, Yongli, Shih, Meng-Chen, Hao, Yilun, Yang, Karen, Srinivasan, Shreyas, Bawendi, Moungi G., Bulovic, Vladimir
We demonstrate a machine learning (ML) approach that accurately predicts the current-voltage behavior of 3D/2D-structured (FAMA)Pb(IBr)3/OABr hybrid organic-inorganic halide perovskite (HOIP) solar cells under AM1.5 illumination. Our neural network a
Externí odkaz:
http://arxiv.org/abs/2412.09638
We propose a novel method for measuring the discrepancy between a set of samples and a desired posterior distribution for Bayesian inference. Classical methods for assessing sample quality like the effective sample size are not appropriate for scalab
Externí odkaz:
http://arxiv.org/abs/2412.05135