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pro vyhledávání: '"Srivastava, Sangeeta"'
Autor:
Srivastava, Sangeeta
Deep neural networks have not only evolved to produce state-of-the-art artificial intelligence (AI) models, but also generalize well, especially when the network has a large capacity and access to a comparable massive training dataset. These models a
Autor:
Srivastava, Sangeeta, Wu, Ho-Hsiang, Rulff, Joao, Fuentes, Magdalena, Cartwright, Mark, Silva, Claudio, Arora, Anish, Bello, Juan Pablo
Audio applications involving environmental sound analysis increasingly use general-purpose audio representations, also known as embeddings, for transfer learning. Recently, Holistic Evaluation of Audio Representations (HEAR) evaluated twenty-nine emb
Externí odkaz:
http://arxiv.org/abs/2203.10425
Autor:
Yun, Jihoon, Srivastava, Sangeeta, Roy, Dhrubojyoti, Stohs, Nathan, Mydlarz, Charlie, Salman, Mahin, Steers, Bea, Bello, Juan Pablo, Arora, Anish
The Sounds of New York City (SONYC) wireless sensor network (WSN) has been fielded in Manhattan and Brooklyn over the past five years, as part of a larger human-in-the-loop cyber-physical control system for monitoring, analyzing, and mitigating urban
Externí odkaz:
http://arxiv.org/abs/2203.06220
Autor:
Srivastava, Sangeeta, Olin, Samuel, Podolskiy, Viktor, Karpatne, Anuj, Lee, Wei-Cheng, Arora, Anish
Given their ability to effectively learn non-linear mappings and perform fast inference, deep neural networks (NNs) have been proposed as a viable alternative to traditional simulation-driven approaches for solving high-dimensional eigenvalue equatio
Externí odkaz:
http://arxiv.org/abs/2202.05994
Autor:
Srivastava, Sangeeta, kumar, Anant, Pandey, Saumya, Kumar, Saurabh, Parveen, Shama, Banerjee, Monisha
Publikováno v:
In Journal of Molecular Structure 15 July 2024 1308
Autor:
Srivastava, Sangeeta, Wang, Yun, Tjandra, Andros, Kumar, Anurag, Liu, Chunxi, Singh, Kritika, Saraf, Yatharth
Representation learning from unlabeled data has been of major interest in artificial intelligence research. While self-supervised speech representation learning has been popular in the speech research community, very few works have comprehensively an
Externí odkaz:
http://arxiv.org/abs/2110.07313
Autor:
Gujjar, Ranjit Singh, Kumar, Rajeev, Goswami, Sanjay Kumar, Srivastava, Sangeeta, Upadhyay, Atul Kumar
Publikováno v:
In Physiological and Molecular Plant Pathology March 2024 130
Autor:
Gujjar, Ranjit Singh, Kumar, Rajeev, Goswami, Sanjay Kumar, Srivastava, Sangeeta, Kumar, Sanjeev
Publikováno v:
In Journal of Proteomics 10 February 2024 292
Autor:
Roy, Dhrubojyoti, Srivastava, Sangeeta, Kusupati, Aditya, Jain, Pranshu, Varma, Manik, Arora, Anish
Edge sensing with micro-power pulse-Doppler radars is an emergent domain in monitoring and surveillance with several smart city applications. Existing solutions for the clutter versus multi-source radar classification task are limited in terms of eit
Externí odkaz:
http://arxiv.org/abs/1909.03082
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