Zobrazeno 1 - 10
of 8 804
pro vyhledávání: '"Ojha P"'
Publikováno v:
Biologics: Targets & Therapy, Vol Volume 18, Pp 257-271 (2024)
Ashok Kumar Patra,1 Shreenath Nayak,1 Anandita Moharana,1 Purusottam Ojha,1 Sanjeet Kumar Das,1 Jabed Akhtar,1 Bishwaranjan Giri,1 Sujay Singh1,2 1Protein Expression Lab, Imgenex India Pvt. Ltd. E-5, Bhubaneswar, Odisha, India; 2Sujan Biologics, Inc.
Externí odkaz:
https://doaj.org/article/79dc5ca6671b47a294836a5f1e833dca
As latent diffusion models (LDMs) democratize image generation capabilities, there is a growing need to detect fake images. A good detector should focus on the generative models fingerprints while ignoring image properties such as semantic content, r
Externí odkaz:
http://arxiv.org/abs/2410.11835
A neutron star (NS) accreting matter from a companion star in a low-mass X-ray binary (LMXB) system can spin up to become a millisecond pulsar (MSP). Properties of many such MSP systems are known, which is excellent for probing fundamental aspects of
Externí odkaz:
http://arxiv.org/abs/2410.08173
Machine-learning technologies are seeing increased deployment in real-world market scenarios. In this work, we explore the strategic behaviors of large language models (LLMs) when deployed as autonomous agents in multi-commodity markets, specifically
Externí odkaz:
http://arxiv.org/abs/2410.00031
Autor:
Reji, Varghese, Kanodia, Shubham, Ninan, Joe, Cañas, Caleb I., Libby-Roberts, Jessica, Lin, Andrea S. J., Gupta, Arvind F, Sewaby, Tera N., Larsen, Alexander, Kobulnicky, Henry A., Choi, Philip I., Evans, Nez, Santomenna, Sage, Winnick, Isabelle, Yu, Larry, Alvarado-Montes, Jaime A., Bender, Chad, Bernabò, Lia Marta, Blake, Cullen H., Cochran, William D., Diddams, Scott A., Halverson, Samuel, Han, Te, Hearty, Fred, Logsdon, Sarah E., Mahadevan, Suvrath, Monson, Andrew, McElwain, Michael, Robertson, Paul, Ojha, Devendra, Roy, Arpita, Schwab, Christian, Stefansson, Gudmundur, Wright, Jason
We present the discovery of a low-density planet transiting TOI-5688 A b, a high-metallicity M2V star. This planet was discovered as part of the search for transiting giant planets ($R \gtrsim8$ M$_\oplus$) through the Searching for GEMS (Giant Exopl
Externí odkaz:
http://arxiv.org/abs/2409.01371
Autor:
Liu, Zhenyu, Duan, Haoran, Liang, Huizhi, Long, Yang, Snasel, Vaclav, Nicosia, Guiseppe, Ranjan, Rajiv, Ojha, Varun
Publikováno v:
31st International Conference on Neural Information Processing (ICONIP), 2024
Adversarial training is one of the most effective methods for enhancing model robustness. Recent approaches incorporate adversarial distillation in adversarial training architectures. However, we notice two scenarios of defense methods that limit the
Externí odkaz:
http://arxiv.org/abs/2408.13102
Autor:
Rawat, Vineet, Samal, M. R., Ojha, D. K., Kumar, Brajesh, Sharma, Saurabh, Jose, J., Sagar, Ram, Yadav, R. K.
We present a detailed near-infrared study of an embedded cluster located in the hub of the giant molecular cloud G148.24+00.41 of mass $\sim$10$^5$ $M_\odot$, with the TANSPEC instrument mounted on the 3.6 m Devasthal Optical Telescope. The hub is lo
Externí odkaz:
http://arxiv.org/abs/2408.12969
Autor:
Zheng, Ziwei, Liang, Huizhi, Snasel, Vaclav, Latora, Vito, Pardalos, Panos, Nicosia, Giuseppe, Ojha, Varun
Publikováno v:
31st International Conference on Neural Information Processing (ICONIP) 2024
We scrutinize the structural and operational aspects of deep learning models, particularly focusing on the nuances of learnable parameters (weight) statistics, distribution, node interaction, and visualization. By establishing correlations between va
Externí odkaz:
http://arxiv.org/abs/2408.11720
Publikováno v:
33rd International Conference on Artificial Neural Networks (ICANN) (2024)
Hierarchical federated learning (HFL) is a promising distributed deep learning model training paradigm, but it has crucial security concerns arising from adversarial attacks. This research investigates and assesses the security of HFL using a novel m
Externí odkaz:
http://arxiv.org/abs/2408.10752
Autor:
Ojha, Divya, Dwarkadas, Sandhya
Shared caches are vulnerable to side channel attacks through contention in cache sets. Besides being a simple source of information leak, these side channels form useful gadgets for more sophisticated attacks that compromise the security of shared sy
Externí odkaz:
http://arxiv.org/abs/2408.08795