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pro vyhledávání: '"Kulkarni, P. V."'
Autor:
Venkataraman, S., Kulkarni, Manisha V.
Let $K=\mathbb{Q}[\iota]$ and $N=K[\sqrt[4]{\alpha}]$, $\alpha\in\mathbb{Z}[\iota]$, $alpha=fg^2h^3$, $f$, $g$, $h\in \mathbb{Z}[\iota]$ are pairwise coprime and square free. Let $\mathcal{O}_N$ be the ring of integers of $N$. In this article we cons
Externí odkaz:
http://arxiv.org/abs/2410.17560
Quantum simulation in its current state faces experimental overhead in terms of physical space and cooling. We propose boson sampling as an alternative compact synthetic platform performing at room temperature. Identifying the capability of estimatin
Externí odkaz:
http://arxiv.org/abs/2410.13938
An agent's ability to leverage past experience is critical for efficiently solving new tasks. Prior work has focused on using value function estimates to obtain zero-shot approximations for solutions to a new task. In soft Q-learning, we show how any
Externí odkaz:
http://arxiv.org/abs/2406.18033
Autor:
Nagrani, Pranay P., Kulkarni, Ritwik V., Kelkar, Parth U., Corder, Ria D., Erk, Kendra A., Marconnet, Amy M., Christov, Ivan C.
Publikováno v:
J. Rheol. 67 (2023) 1129--1140
Thermal greases, often used as thermal interface materials, are complex paste-like mixtures composed of a base polymer in which dense metallic (or ceramic) filler particles are dispersed to improve the heat transfer properties of the material. They h
Externí odkaz:
http://arxiv.org/abs/2304.12104
In the field of reinforcement learning (RL), agents are often tasked with solving a variety of problems differing only in their reward functions. In order to quickly obtain solutions to unseen problems with new reward functions, a popular approach in
Externí odkaz:
http://arxiv.org/abs/2303.02557
In reinforcement learning (RL), the ability to utilize prior knowledge from previously solved tasks can allow agents to quickly solve new problems. In some cases, these new problems may be approximately solved by composing the solutions of previously
Externí odkaz:
http://arxiv.org/abs/2212.01174
Autor:
Dessai, Malati, Kulkarni, Arun V.
The Planar Model of the Electrode-Vacuum-Electrode configuration for STM in which electrode surfaces are assumed to be infinite parallel planes, with atomic size separation and vacuum between them, is used to calculate tunneling current densities for
Externí odkaz:
http://arxiv.org/abs/2204.04122
Publikováno v:
Phys. Rev. Research 5, 023085 (2023)
Reinforcement learning (RL) is an important field of research in machine learning that is increasingly being applied to complex optimization problems in physics. In parallel, concepts from physics have contributed to important advances in RL with dev
Externí odkaz:
http://arxiv.org/abs/2106.03931
Autor:
Kulkarni, Giridhar V.
Since a long-time, the quantum integrable systems have remained an area where modern mathematical methods have given an access to interesting results in the study of physical systems. The exact computations, both numerical and asymptotic, of the corr
Externí odkaz:
http://arxiv.org/abs/2012.02367
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