Zobrazeno 1 - 10
of 41 399
pro vyhledávání: '"A Purohit"'
This paper proposes a framework of explaining anomalous machine sounds in the context of anomalous sound detection~(ASD). While ASD has been extensively explored, identifying how anomalous sounds differ from normal sounds is also beneficial for machi
Externí odkaz:
http://arxiv.org/abs/2410.22033
Autor:
Purohit, Abhishek, Christen, Jose Jorge, Kienhoefer, Richard, Armstrong, Simon, Kaur, Maninder, Venegas-Gomez, Araceli
As nations and organisations worldwide intensify their efforts and investments to commercialise quantum technologies and explore practical applications across various industries, there is a burgeoning demand for skilled professionals to support this
Externí odkaz:
http://arxiv.org/abs/2410.21219
Autor:
Hota, Ananda, Dabhade, Pratik, Machado, Prasun, Kumar, Avinash, Avinash, Ck., Manaswini, Ninisha, Das, Joydeep, Sethi, Sagar, Sahoo, Sumanta, Dubal, Shilpa, Bhoga, Sai Arun Dharmik, Navaneeth, P. K., Konar, C., Pal, Sabyasachi, Vaddi, Sravani, Apoorva, Prakash, Rajoria, Megha, Purohit, Arundhati
Understanding the evolution of galaxies cannot exclude the important role played by the central supermassive black hole and the circumgalactic medium (CGM). Simulations have strongly suggested the negative feedback of AGN Jet/wind/outflows on the ISM
Externí odkaz:
http://arxiv.org/abs/2410.10294
In Clique Cover, given a graph $G$ and an integer $k$, the task is to partition the vertices of $G$ into $k$ cliques. Clique Cover on unit ball graphs has a natural interpretation as a clustering problem, where the objective function is the maximum d
Externí odkaz:
http://arxiv.org/abs/2410.03609
Posterior sampling in high-dimensional spaces using generative models holds significant promise for various applications, including but not limited to inverse problems and guided generation tasks. Despite many recent developments, generating diverse
Externí odkaz:
http://arxiv.org/abs/2410.02078
MIMII-Gen: Generative Modeling Approach for Simulated Evaluation of Anomalous Sound Detection System
Insufficient recordings and the scarcity of anomalies present significant challenges in developing and validating robust anomaly detection systems for machine sounds. To address these limitations, we propose a novel approach for generating diverse an
Externí odkaz:
http://arxiv.org/abs/2409.18542
Due to scarcity of time-series data annotated with descriptive texts, training a model to generate descriptive texts for time-series data is challenging. In this study, we propose a method to systematically generate domain-independent descriptive tex
Externí odkaz:
http://arxiv.org/abs/2409.16647
The integration of the Internet of Things (IoT) into Cyber-Physical Systems (CPSs) has expanded their cyber-attack surface, introducing new and sophisticated threats with potential to exploit emerging vulnerabilities. Assessing the risks of CPSs is i
Externí odkaz:
http://arxiv.org/abs/2409.16176
Autor:
Nazarczuk, Michal, Catley-Chandar, Sibi, Tanay, Thomas, Shaw, Richard, Pérez-Pellitero, Eduardo, Timofte, Radu, Yan, Xing, Wang, Pan, Guo, Yali, Wu, Yongxin, Cai, Youcheng, Yang, Yanan, Li, Junting, Zhou, Yanghong, Mok, P. Y., He, Zongqi, Xiao, Zhe, Chan, Kin-Chung, Goshu, Hana Lebeta, Yang, Cuixin, Dong, Rongkang, Xiao, Jun, Lam, Kin-Man, Hao, Jiayao, Gao, Qiong, Zu, Yanyan, Zhang, Junpei, Jiao, Licheng, Liu, Xu, Purohit, Kuldeep
This paper reviews the challenge on Sparse Neural Rendering that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2024. This manuscript focuses on the competition set-up, the proposed methods and their resp
Externí odkaz:
http://arxiv.org/abs/2409.15045
Deep convolutional neural networks (CNNs) have achieved impressive performance in many computer vision tasks. However, their large model sizes require heavy computational resources, making pruning redundant filters from existing pre-trained CNNs an e
Externí odkaz:
http://arxiv.org/abs/2409.03777