Zobrazeno 1 - 10
of 51
pro vyhledávání: '"RANJAN, ADITYA"'
Driven by swift progress in hardware capabilities, quantum machine learning has emerged as a research area of interest. Recently, quantum image generation has produced promising results. However, prior quantum image generation techniques rely on clas
Externí odkaz:
http://arxiv.org/abs/2409.19823
Autor:
Silver, Daniel, Patel, Tirthak, Ranjan, Aditya, Gandhi, Harshitta, Cutler, William, Tiwari, Devesh
Publikováno v:
Vol. 37 No. 8: AAAI-2023 Technical Tracks 8
Exploration into quantum machine learning has grown tremendously in recent years due to the ability of quantum computers to speed up classical programs. However, these efforts have yet to solve unsupervised similarity detection tasks due to the chall
Externí odkaz:
http://arxiv.org/abs/2309.15259
Autor:
Silver, Daniel, Patel, Tirthak, Cutler, William, Ranjan, Aditya, Gandhi, Harshitta, Tiwari, Devesh
Quantum machine learning and vision have come to the fore recently, with hardware advances enabling rapid advancement in the capabilities of quantum machines. Recently, quantum image generation has been explored with many potential advantages over no
Externí odkaz:
http://arxiv.org/abs/2308.11096
Autor:
Patel, Tirthak, Silver, Daniel, Ranjan, Aditya, Gandhi, Harshitta, Cutler, William, Tiwari, Devesh
Quantum computing is an emerging paradigm that has shown great promise in accelerating large-scale scientific, optimization, and machine-learning workloads. With most quantum computing solutions being offered over the cloud, it has become imperative
Externí odkaz:
http://arxiv.org/abs/2307.16799
Performance analysis is a critical step in the oft-repeated, iterative process of performance tuning of parallel programs. Per-process, per-thread traces (detailed logs of events with timestamps) enable in-depth analysis of parallel program execution
Externí odkaz:
http://arxiv.org/abs/2306.11177
Heavy communication, in particular, collective operations, can become a critical performance bottleneck in scaling the training of billion-parameter neural networks to large-scale parallel systems. This paper introduces a four-dimensional (4D) approa
Externí odkaz:
http://arxiv.org/abs/2305.13525
Autor:
Senthan, S., Ananthi, S., Ranjan, Aditya, Ibragimov, A.B., Guganathan, L., Bhuvaneshwari, S., Suppuraj, P., Normamatov, A.S., Balakrishnan, C.
Publikováno v:
In Journal of Solid State Chemistry December 2024 340
Autor:
Ranjan, Aditya Kaushal, Kumar, Prabhat
Publikováno v:
In Ad Hoc Networks 1 November 2024 164
Autor:
Ranjan, Aditya Kaushal, Kumar, Prabhat
Publikováno v:
Multimedia Tools & Applications; Oct2024, Vol. 83 Issue 33, p79067-79092, 26p
Publikováno v:
Drug Delivery & Translational Research; Sep2024, Vol. 14 Issue 9, p2558-2577, 20p