Zobrazeno 1 - 10
of 1 072
pro vyhledávání: '"Héroux P"'
Autor:
Piquenot, Jason, Bérar, Maxime, Héroux, Pierre, Ramel, Jean-Yves, Raveaux, Romain, Adam, Sébastien
This paper presents Grammar Reinforcement Learning (GRL), a reinforcement learning algorithm that uses Monte Carlo Tree Search (MCTS) and a transformer architecture that models a Pushdown Automaton (PDA) within a context-free grammar (CFG) framework.
Externí odkaz:
http://arxiv.org/abs/2410.01661
Autor:
Heroux, Michael A.
The Exascale Computing Project (ECP) was one of the largest open-source scientific software development projects ever. It supported approximately 1,000 staff from US Department of Energy laboratories, and university and industry partners. About 250 s
Externí odkaz:
http://arxiv.org/abs/2311.06995
Autor:
McInnes, Lois Curfman, Heroux, Michael, Bernholdt, David E., Dubey, Anshu, Gonsiorowski, Elsa, Gupta, Rinku, Marques, Osni, Moulton, J. David, Nam, Hai Ah, Norris, Boyana, Raybourn, Elaine M., Willenbring, Jim, Almgren, Ann, Bartlett, Ross, Cranfill, Kita, Fickas, Stephen, Frederick, Don, Godoy, William, Grubel, Patricia, Hartman-Baker, Rebecca, Huebl, Axel, Lynch, Rose, Thakur, Addi Malviya, Milewicz, Reed, Miller, Mark C., Mundt, Miranda, Palmer, Erik, Parete-Koon, Suzanne, Phinney, Megan, Riley, Katherine, Rogers, David M., Sims, Ben, Stevens, Deborah, Watson, Gregory R.
Computational and data-enabled science and engineering are revolutionizing advances throughout science and society, at all scales of computing. For example, teams in the U.S. DOE Exascale Computing Project have been tackling new frontiers in modeling
Externí odkaz:
http://arxiv.org/abs/2311.02010
Autor:
Piquenot, Jason, Moscatelli, Aldo, Bérar, Maxime, Héroux, Pierre, raveaux, Romain, Ramel, Jean-Yves, Adam, Sébastien
This paper introduces a framework for formally establishing a connection between a portion of an algebraic language and a Graph Neural Network (GNN). The framework leverages Context-Free Grammars (CFG) to organize algebraic operations into generative
Externí odkaz:
http://arxiv.org/abs/2303.01590
Autor:
Heroux, Michael A.
Software plays a central role in scientific discovery. Improving how we develop and use software for research can have both broad and deep impacts on a spectrum of challenges and opportunities society faces today. The emergence of Research Software E
Externí odkaz:
http://arxiv.org/abs/2211.09034
Autor:
Jiamin Zhong, Lihuan Zhang, Kelie Chen, Xiaoyu Yuan, Zhenyan Cui, Song Tang, Fang Zheng, Ying Li, Paul Héroux, Yihua Wu, Dajing Xia
Publikováno v:
Ecotoxicology and Environmental Safety, Vol 284, Iss , Pp 116907- (2024)
Perfluorononanoic acid (PFNA), an acknowledged environmental endocrine disruptor, is increasingly utilized as a substitute for perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA). Despite its growing use, limited research has been c
Externí odkaz:
https://doaj.org/article/b81e28196f2146519e3948f1b141d85b
Autor:
Joel M. Moskowitz, John W. Frank, Ronald L. Melnick, Lennart Hardell, Igor Belyaev, Paul Héroux, Elizabeth Kelley, Henry Lai, Don Maisch, Erica Mallery-Blythe, Alasdair Philips
Publikováno v:
Environment International, Vol 190, Iss , Pp 108807- (2024)
Externí odkaz:
https://doaj.org/article/c7597425cd9448de8e1853bc126b4aee
Publikováno v:
Frontiers in Psychology, Vol 15 (2024)
This pan-Canadian study investigates the effects of musical practice on the well-being, mental health, and social support of Canadian musicians during the COVID-19 pandemic. Using a survey questionnaire, data was collected from 1,618 participants age
Externí odkaz:
https://doaj.org/article/e9e1e15a8ee749acbcd443f4e8f5c8b3
Autor:
Balcilar, Muhammet, Héroux, Pierre, Gaüzère, Benoit, Vasseur, Pascal, Adam, Sébastien, Honeine, Paul
Publikováno v:
The Thirty-eighth International Conference on Machine Learning, ICML2021
Since the Message Passing (Graph) Neural Networks (MPNNs) have a linear complexity with respect to the number of nodes when applied to sparse graphs, they have been widely implemented and still raise a lot of interest even though their theoretical ex
Externí odkaz:
http://arxiv.org/abs/2106.04319
Autor:
Balcilar, Muhammet, Renton, Guillaume, Heroux, Pierre, Gauzere, Benoit, Adam, Sebastien, Honeine, Paul
This paper aims at revisiting Graph Convolutional Neural Networks by bridging the gap between spectral and spatial design of graph convolutions. We theoretically demonstrate some equivalence of the graph convolution process regardless it is designed
Externí odkaz:
http://arxiv.org/abs/2003.11702