no code implementations • 22 Aug 2023 • OoLEN, Silke Asche, Carla Bautista, David Boulesteix, Alexandre Champagne-Ruel, Cole Mathis, Omer Markovitch, Zhen Peng, Alyssa Adams, Avinash Vicholous Dass, Arnaud Buch, Eloi Camprubi, Enrico Sandro Colizzi, Stephanie Colón-Santos, Hannah Dromiack, Valentina Erastova, Amanda Garcia, Ghjuvan Grimaud, Aaron Halpern, Stuart A Harrison, Seán F. Jordan, Tony Z Jia, Amit Kahana, Artemy Kolchinsky, Odin Moron-Garcia, Ryo Mizuuchi, Jingbo Nan, Yuliia Orlova, Ben K. D. Pearce, Klaus Paschek, Martina Preiner, Silvana Pinna, Eduardo Rodríguez-Román, Loraine Schwander, Siddhant Sharma, Harrison B. Smith, Andrey Vieira, Joana C. Xavier
The sheer number of different scientific perspectives relevant to the problem has resulted in the coexistence of diverse tools, techniques, data, and software in OoL studies.
no code implementations • CVPR 2023 • Shen Yan, Yu Liu, Long Wang, Zehong Shen, Zhen Peng, Haomin Liu, Maojun Zhang, Guofeng Zhang, Xiaowei Zhou
Despite the remarkable advances in image matching and pose estimation, image-based localization of a camera in a temporally-varying outdoor environment is still a challenging problem due to huge appearance disparity between query and reference images caused by illumination, seasonal and structural changes.
1 code implementation • IEEE Open Journal of Antennas and Propagation 2020 • Oameed Noakoasteen, Shu Wang, Zhen Peng, Christos Christodoulou
In this paper, we propose a deep neural network based model to predict the time evolution of field values in transient electrodynamics.
no code implementations • 3 Mar 2020 • Zhen Peng, Yixiang Dong, Minnan Luo, Xiao-Ming Wu, Qinghua Zheng
To take full advantage of fast-growing unlabeled networked data, this paper introduces a novel self-supervised strategy for graph representation learning by exploiting natural supervision provided by the data itself.
1 code implementation • 4 Feb 2020 • Zhen Peng, Wenbing Huang, Minnan Luo, Qinghua Zheng, Yu Rong, Tingyang Xu, Junzhou Huang
The richness in the content of various information networks such as social networks and communication networks provides the unprecedented potential for learning high-quality expressive representations without external supervision.
no code implementations • 16 Apr 2018 • Zhen Peng, Tim Genewein, Felix Leibfried, Daniel A. Braun
Here we consider perception and action as two serial information channels with limited information-processing capacity.