Zobrazeno 1 - 10
of 556
pro vyhledávání: '"Deng, BoWen"'
Autor:
Deng, Bowen, Choi, Yunyeong, Zhong, Peichen, Riebesell, Janosh, Anand, Shashwat, Li, Zhuohan, Jun, KyuJung, Persson, Kristin A., Ceder, Gerbrand
Machine learning interatomic potentials (MLIPs) have introduced a new paradigm for atomic simulations. Recent advancements have seen the emergence of universal MLIPs (uMLIPs) that are pre-trained on diverse materials datasets, providing opportunities
Externí odkaz:
http://arxiv.org/abs/2405.07105
Autor:
Deng, Bowen, Zhang, Yihan, Parkes, Andrew, Bentley, Alex, Wright, Amanda, Pound, Michael, Somekh, Michael
Estimation of the optical properties of scattering media such as tissue is important in diagnostics as well as in the development of techniques to image deeper. As light penetrates the sample scattering events occur that alter the propagation directi
Externí odkaz:
http://arxiv.org/abs/2404.16647
Among the chloride-based Li-ion solid electrolytes, Li$_2$ZrCl$_6$ (LZC) have emerged as potential candidates due to their affordability, moisture stability, and high ionic conductivity. LZC synthesized by solid-state heating exhibits limited Li-ion
Externí odkaz:
http://arxiv.org/abs/2403.08237
Autor:
Riebesell, Janosh, Goodall, Rhys E. A., Benner, Philipp, Chiang, Yuan, Deng, Bowen, Lee, Alpha A., Jain, Anubhav, Persson, Kristin A.
Matbench Discovery simulates the deployment of machine learning (ML) energy models in a high-throughput search for stable inorganic crystals. We address the disconnect between (i) thermodynamic stability and formation energy and (ii) in-domain vs out
Externí odkaz:
http://arxiv.org/abs/2308.14920
Autor:
Deng, Bowen
The integration of artificial intelligence and science has resulted in substantial progress in computational chemistry methods for the design and discovery of novel catalysts. Nonetheless, the challenges of electrocatalytic reactions and developing a
Externí odkaz:
http://arxiv.org/abs/2305.19545
Anomaly detection on attributed graphs is a crucial topic for its practical application. Existing methods suffer from semantic mixture and imbalance issue because they mainly focus on anomaly discrimination, ignoring representation learning. It confl
Externí odkaz:
http://arxiv.org/abs/2304.05176
Artificial intelligence (AI) has emerged as a tool for discovering and optimizing novel battery materials. However, the adoption of AI in battery cathode representation and discovery is still limited due to the complexity of optimizing multiple perfo
Externí odkaz:
http://arxiv.org/abs/2304.04986
Autor:
Deng, Bowen, Zhong, Peichen, Jun, KyuJung, Riebesell, Janosh, Han, Kevin, Bartel, Christopher J., Ceder, Gerbrand
The simulation of large-scale systems with complex electron interactions remains one of the greatest challenges for the atomistic modeling of materials. Although classical force fields often fail to describe the coupling between electronic states and
Externí odkaz:
http://arxiv.org/abs/2302.14231
Graph analysts cannot directly obtain the global structure in decentralized social networks, and analyzing such a network requires collecting local views of the social graph from individual users. Since the edges between users may reveal sensitive so
Externí odkaz:
http://arxiv.org/abs/2212.05253
Autor:
Deng, Bowen1 (AUTHOR) dengbowen8693@outlook.com, Liu, Qingcheng2 (AUTHOR), Qiao, Liang1 (AUTHOR), Lv, Shun1 (AUTHOR)
Publikováno v:
PLoS ONE. 9/13/2024 c, Vol. 19 Issue 9, p1-15. 15p.
