Zobrazeno 1 - 10
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pro vyhledávání: '"Khare A"'
Graphical models have found widespread applications in many areas of modern statistics and machine learning. Iterative Proportional Fitting (IPF) and its variants have become the default method for undirected graphical model estimation, and are thus
Externí odkaz:
http://arxiv.org/abs/2408.11718
Autor:
Kell, Gregory, Roberts, Angus, Umansky, Serge, Khare, Yuti, Ahmed, Najma, Patel, Nikhil, Simela, Chloe, Coumbe, Jack, Rozario, Julian, Griffiths, Ryan-Rhys, Marshall, Iain J.
Clinical question answering systems have the potential to provide clinicians with relevant and timely answers to their questions. Nonetheless, despite the advances that have been made, adoption of these systems in clinical settings has been slow. One
Externí odkaz:
http://arxiv.org/abs/2408.08624
Motivated by the recent introduction of an integrable coupled massive Thirring model by Basu-Mallick et al, we introduce a new coupled Soler model. Further we generalize both the coupled massive Thirring and the coupled Soler model to arbitrary nonli
Externí odkaz:
http://arxiv.org/abs/2407.16596
Autor:
Annavajjala, Aditya, Khare, Alind, Agrawal, Animesh, Fedorov, Igor, Latapie, Hugo, Lee, Myungjin, Tumanov, Alexey
CNNs are increasingly deployed across different hardware, dynamic environments, and low-power embedded devices. This has led to the design and training of CNN architectures with the goal of maximizing accuracy subject to such variable deployment cons
Externí odkaz:
http://arxiv.org/abs/2407.06167
We study how to subvert language models from following the rules. We model rule-following as inference in propositional Horn logic, a mathematical system in which rules have the form "if $P$ and $Q$, then $R$" for some propositions $P$, $Q$, and $R$.
Externí odkaz:
http://arxiv.org/abs/2407.00075
Autor:
Wornow, Michael, Narayan, Avanika, Viggiano, Ben, Khare, Ishan S., Verma, Tathagat, Thompson, Tibor, Hernandez, Miguel Angel Fuentes, Sundar, Sudharsan, Trujillo, Chloe, Chawla, Krrish, Lu, Rongfei, Shen, Justin, Nagaraj, Divya, Martinez, Joshua, Agrawal, Vardhan, Hudson, Althea, Shah, Nigam H., Re, Christopher
Existing ML benchmarks lack the depth and diversity of annotations needed for evaluating models on business process management (BPM) tasks. BPM is the practice of documenting, measuring, improving, and automating enterprise workflows. However, resear
Externí odkaz:
http://arxiv.org/abs/2406.13264
The data augmentation (DA) algorithms are popular Markov chain Monte Carlo (MCMC) algorithms often used for sampling from intractable probability distributions. This review article comprehensively surveys DA MCMC algorithms, highlighting their theore
Externí odkaz:
http://arxiv.org/abs/2406.10464
Recently, neutral atoms have emerged as a promising platform for quantum computing, offering scalability. In this study, we showcase the realization of atomic qubits in atom-molecular Bose-Einstein condensate, belonging to three distinct classes. In
Externí odkaz:
http://arxiv.org/abs/2406.01177
The objective of this work is to assess the impact of parameter uncertainty on hypersonic aerothermal surface heating predictions in Reynolds-Averaged Navier-Stokes (RANS) simulations using non-intrusive uncertainty quantification (UQ) techniques. RA
Externí odkaz:
http://arxiv.org/abs/2405.15875
The rapid advancement in Large Language Models has been met with significant challenges in their training processes, primarily due to their considerable computational and memory demands. This research examines parallelization techniques developed to
Externí odkaz:
http://arxiv.org/abs/2405.15628