no code implementations • 25 Apr 2024 • Bowen Deng, Yihan Zhang, Andrew Parkes, Alex Bentley, Amanda Wright, Michael Pound, Michael Somekh
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.
2 code implementations • 28 Aug 2023 • Janosh Riebesell, Rhys E. A. Goodall, Philipp Benner, Yuan Chiang, Bowen Deng, Alpha A. Lee, Anubhav Jain, Kristin A. Persson
The top 3 models are UIPs, the winning methodology for ML-guided materials discovery, achieving F1 scores of ~0. 6 for crystal stability classification and discovery acceleration factors (DAF) of up to 5x on the first 10k most stable predictions compared to dummy selection from our test set.
no code implementations • 31 May 2023 • Bowen Deng
To address the challenge of limited data in catalysis, we propose a machine learning approach based on MLP-Like and a framework called Catalysis Distillation Graph Neural Network (CDGNN).
no code implementations • 11 Apr 2023 • YanMing Hu, Chuan Chen, Bowen Deng, YuJing Lai, Hao Lin, Zibin Zheng, Jing Bian
DSLAD is a self-supervised method with anomaly discrimination and representation learning decoupled for anomaly detection.
1 code implementation • 28 Feb 2023 • Bowen Deng, Peichen Zhong, KyuJung Jun, Janosh Riebesell, Kevin Han, Christopher J. Bartel, Gerbrand Ceder
The simulation of large-scale systems with complex electron interactions remains one of the greatest challenges for the atomistic modeling of materials.
1 code implementation • 7 Jun 2022 • Bowen Deng, Dongchang Liu
Temporal Action Detection(TAD) is a crucial but challenging task in video understanding. It is aimed at detecting both the type and start-end frame for each action instance in a long, untrimmed video. Most current models adopt both RGB and Optical-Flow streams for the TAD task.
Ranked #2 on Action Detection on THUMOS' 14
no code implementations • 23 Jan 2022 • Zheren Wang, Kevin Cruse, Yuxing Fei, Ann Chia, Yan Zeng, Haoyan Huo, Tanjin He, Bowen Deng, Olga Kononova, Gerbrand Ceder
This work is an important step towards creating a synthesis ontology and a solid foundation for autonomous robotic synthesis.
1 code implementation • 4 Nov 2021 • Bowen Deng, Andrew P. French, Michael P. Pound
In this paper, we directly address the problem of detecting multiple salient objects across complex scenes.
no code implementations • 23 May 2018 • Pengcheng Yin, Bowen Deng, Edgar Chen, Bogdan Vasilescu, Graham Neubig
For tasks like code synthesis from natural language, code retrieval, and code summarization, data-driven models have shown great promise.