Zobrazeno 1 - 10
of 17 213
pro vyhledávání: '"A. Vasanth"'
Publikováno v:
In Microprocessors and Microsystems November 2019 71
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Aitokhuehi, Ayo, Braiman, Benjamin, Cutler, David Owen Horace, Darvas, Tamás, Deaton, Robert, Gupta, Prakhar, Horsley, Jude, Pidaparthy, Vasanth, Tang, Jen
Given a compact K\"ahler manifold $(X,\omega)$, due to the work of Darvas-Di Nezza-Lu, the space of singularity types of $\omega$-psh functions admits a natural pseudo-metric $d_\mathcal S$ that is complete in the presence of positive mass. When rest
Externí odkaz:
http://arxiv.org/abs/2411.11246
Autor:
Goldowsky, Howard, Sarathy, Vasanth
We propose an approach to analogical inference that marries the neuro-symbolic computational power of complex-sampled hyperdimensional computing (HDC) with Conceptual Spaces Theory (CST), a promising theory of semantic meaning. CST sketches, at an ab
Externí odkaz:
http://arxiv.org/abs/2411.08684
Turn-taking is a fundamental mechanism in human communication that ensures smooth and coherent verbal interactions. Recent advances in Large Language Models (LLMs) have motivated their use in improving the turn-taking capabilities of Spoken Dialogue
Externí odkaz:
http://arxiv.org/abs/2410.16044
Large Language Models (LLMs), despite achieving state-of-the-art results in a number of evaluation tasks, struggle to maintain their performance when logical reasoning is strictly required to correctly infer a prediction. In this work, we propose Arg
Externí odkaz:
http://arxiv.org/abs/2410.12997
Liquid-droplet coalescence and the mergers of liquid lenses are problems of great practical and theoretical interest in fluid dynamics and the statistical mechanics of multi-phase flows. During such mergers, there is an interesting and intricate inte
Externí odkaz:
http://arxiv.org/abs/2410.04451
Many real-world problems, such as controlling swarms of drones and urban traffic, naturally lend themselves to modeling as multi-agent reinforcement learning (RL) problems. However, existing multi-agent RL methods often suffer from scalability challe
Externí odkaz:
http://arxiv.org/abs/2410.02516
Multi-agent reinforcement learning for the control of three-dimensional Rayleigh-B\'enard convection
Autor:
Vasanth, Joel, Rabault, Jean, Alcántara-Ávila, Francisco, Mortensen, Mikael, Vinuesa, Ricardo
Deep reinforcement learning (DRL) has found application in numerous use-cases pertaining to flow control. Multi-agent RL (MARL), a variant of DRL, has shown to be more effective than single-agent RL in controlling flows exhibiting locality and transl
Externí odkaz:
http://arxiv.org/abs/2407.21565
Autor:
Jeon, Joongoo, Rabault, Jean, Vasanth, Joel, Alcántara-Ávila, Francisco, Baral, Shilaj, Vinuesa, Ricardo
Flow control is key to maximize energy efficiency in a wide range of applications. However, traditional flow-control methods face significant challenges in addressing non-linear systems and high-dimensional data, limiting their application in realist
Externí odkaz:
http://arxiv.org/abs/2407.17822