Zobrazeno 1 - 10
of 7 083
pro vyhledávání: '"A. Vasanth"'
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
Autor:
Nvidia, Adler, Bo, Agarwal, Niket, Aithal, Ashwath, Anh, Dong H., Bhattacharya, Pallab, Brundyn, Annika, Casper, Jared, Catanzaro, Bryan, Clay, Sharon, Cohen, Jonathan, Das, Sirshak, Dattagupta, Ayush, Delalleau, Olivier, Derczynski, Leon, Dong, Yi, Egert, Daniel, Evans, Ellie, Ficek, Aleksander, Fridman, Denys, Ghosh, Shaona, Ginsburg, Boris, Gitman, Igor, Grzegorzek, Tomasz, Hero, Robert, Huang, Jining, Jawa, Vibhu, Jennings, Joseph, Jhunjhunwala, Aastha, Kamalu, John, Khan, Sadaf, Kuchaiev, Oleksii, LeGresley, Patrick, Li, Hui, Liu, Jiwei, Liu, Zihan, Long, Eileen, Mahabaleshwarkar, Ameya Sunil, Majumdar, Somshubra, Maki, James, Martinez, Miguel, de Melo, Maer Rodrigues, Moshkov, Ivan, Narayanan, Deepak, Narenthiran, Sean, Navarro, Jesus, Nguyen, Phong, Nitski, Osvald, Noroozi, Vahid, Nutheti, Guruprasad, Parisien, Christopher, Parmar, Jupinder, Patwary, Mostofa, Pawelec, Krzysztof, Ping, Wei, Prabhumoye, Shrimai, Roy, Rajarshi, Saar, Trisha, Sabavat, Vasanth Rao Naik, Satheesh, Sanjeev, Scowcroft, Jane Polak, Sewall, Jason, Shamis, Pavel, Shen, Gerald, Shoeybi, Mohammad, Sizer, Dave, Smelyanskiy, Misha, Soares, Felipe, Sreedhar, Makesh Narsimhan, Su, Dan, Subramanian, Sandeep, Sun, Shengyang, Toshniwal, Shubham, Wang, Hao, Wang, Zhilin, You, Jiaxuan, Zeng, Jiaqi, Zhang, Jimmy, Zhang, Jing, Zhang, Vivienne, Zhang, Yian, Zhu, Chen
We release the Nemotron-4 340B model family, including Nemotron-4-340B-Base, Nemotron-4-340B-Instruct, and Nemotron-4-340B-Reward. Our models are open access under the NVIDIA Open Model License Agreement, a permissive model license that allows distri
Externí odkaz:
http://arxiv.org/abs/2406.11704
Physically-based renderings contain Monte-Carlo noise, with variance that increases as the number of rays per pixel decreases. This noise, while zero-mean for good modern renderers, can have heavy tails (most notably, for scenes containing specular o
Externí odkaz:
http://arxiv.org/abs/2404.00491