Zobrazeno 1 - 10
of 751
pro vyhledávání: '"JHA, NIRAJ K."'
Autor:
Li, Chia-Hao, Jha, Niraj K.
Wearable medical sensors (WMSs) are revolutionizing smart healthcare by enabling continuous, real-time monitoring of user physiological signals, especially in the field of consumer healthcare. The integration of WMSs and modern machine learning (ML)
Externí odkaz:
http://arxiv.org/abs/2409.09549
Autor:
Yue, Chang, Jha, Niraj K.
The ubiquity of neural networks (NNs) in real-world applications, from healthcare to natural language processing, underscores their immense utility in capturing complex relationships within high-dimensional data. However, NNs come with notable disadv
Externí odkaz:
http://arxiv.org/abs/2407.04168
Autor:
Lala, Sayeri, Jha, Niraj K.
Clinical randomized controlled trials (RCTs) collect hundreds of measurements spanning various metric types (e.g., laboratory tests, cognitive/motor assessments, etc.) across 100s-1000s of subjects to evaluate the effect of a treatment, but do so at
Externí odkaz:
http://arxiv.org/abs/2406.16351
Deep neural networks exhibit remarkable performance, yet their black-box nature limits their utility in fields like healthcare where interpretability is crucial. Existing explainability approaches often sacrifice accuracy and lack quantifiable measur
Externí odkaz:
http://arxiv.org/abs/2406.00539
Diffusion Models (DMs) have exhibited superior performance in generating high-quality and diverse images. However, this exceptional performance comes at the cost of expensive architectural design, particularly due to the attention module heavily used
Externí odkaz:
http://arxiv.org/abs/2405.05252
Traditional language models operate autoregressively, i.e., they predict one token at a time. Rapid explosion in model sizes has resulted in high inference times. In this work, we propose DynaMo, a suite of multi-token prediction language models that
Externí odkaz:
http://arxiv.org/abs/2405.00888
Autor:
Li, Chia-Hao, Jha, Niraj K.
We propose PAGE, a domain-incremental adaptation strategy with past-agnostic generative replay for smart healthcare. PAGE enables generative replay without the aid of any preserved data or information from prior domains. When adapting to a new domain
Externí odkaz:
http://arxiv.org/abs/2403.08197
Autor:
Dedhia, Bhishma, Jha, Niraj K.
Several accounts of human cognition posit that our intelligence is rooted in our ability to form abstract composable concepts, ground them in our environment, and reason over these grounded entities. This trifecta of human thought has remained elusiv
Externí odkaz:
http://arxiv.org/abs/2403.07887
Autor:
Lala, Sayeri, Jha, Niraj K.
Phase-3 clinical trials provide the highest level of evidence on drug safety and effectiveness needed for market approval by implementing large randomized controlled trials (RCTs). However, 30-40% of these trials fail mainly because such studies have
Externí odkaz:
http://arxiv.org/abs/2401.03693
Autor:
Tuli, Shikhar, Jha, Niraj K.
Researchers constantly strive to explore larger and more complex search spaces in various scientific studies and physical experiments. However, such investigations often involve sophisticated simulators or time-consuming experiments that make explori
Externí odkaz:
http://arxiv.org/abs/2308.08666