Zobrazeno 1 - 10
of 560
pro vyhledávání: '"Gupta Yash"'
This work proposes a novel and efficient quadstream BiLSTM-Attention network, abbreviated as QSLA network, for robust automatic modulation classification (AMC) of wireless signals. The proposed model exploits multiple representations of the wireless
Externí odkaz:
http://arxiv.org/abs/2408.07247
Several recent works have studied the societal effects of AI; these include issues such as fairness, robustness, and safety. In many of these objectives, a learner seeks to minimize its worst-case loss over a set of predefined distributions (known as
Externí odkaz:
http://arxiv.org/abs/2310.18832
This paper examines the effects of inherent risks in the emerging technology of non-fungible tokens and proposes an actionable set of solutions for stakeholders in this ecosystem and observers. Web3 and NFTs are a fast-growing 300 billion dollar econ
Externí odkaz:
http://arxiv.org/abs/2204.01487
Publikováno v:
In Journal of Hydrology November 2024 644
Autor:
Kumar, Jatin, Kumar, Ankit, Gupta, Yash, Vashisht, Kapil, Kumar, Shivam, Sharma, Arvind, Kumar, Raj, Sharon, Ashoke, Tripathi, Praveen K., Das, Ram, Singh, Om Prakash, Singh, Shailja, Chakraborti, Soumyananda, Sunil, Sujatha, Pandey, Kailash C.
Publikováno v:
In Journal of Biological Chemistry October 2024 300(10)
Publikováno v:
In The American Journal of Pathology September 2024 194(9):1664-1683
Publikováno v:
In Computers in Human Behavior September 2024 158
Autor:
Kumar, Vishwajeet, Gupta, Yash, Chemmengath, Saneem, Sen, Jaydeep, Chakrabarti, Soumen, Bharadwaj, Samarth, Pan, FeiFei
Question answering (QA) over tables and linked text, also called TextTableQA, has witnessed significant research in recent years, as tables are often found embedded in documents along with related text. HybridQA and OTT-QA are the two best-known Text
Externí odkaz:
http://arxiv.org/abs/2112.07337
Autor:
Gupta, Yash, Sohail Khan, Mohammad, Bansal, Mansi, Kumar Singh, Manish, Pragatheesh, K, Thakur, Archana
Publikováno v:
In Results in Chemistry August 2024 10
Machine-Learning-as-a-Service providers expose machine learning (ML) models through application programming interfaces (APIs) to developers. Recent work has shown that attackers can exploit these APIs to extract good approximations of such ML models,
Externí odkaz:
http://arxiv.org/abs/2107.05166