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pro vyhledávání: '"LIU, GUOQING"'
Autor:
Maziarz, Krzysztof, Liu, Guoqing, Misztela, Hubert, Kornev, Aleksei, Gaiński, Piotr, Hoefling, Holger, Fortunato, Mike, Gupta, Rishi, Segler, Marwin
Planning and conducting chemical syntheses remains a major bottleneck in the discovery of functional small molecules, and prevents fully leveraging generative AI for molecular inverse design. While early work has shown that ML-based retrosynthesis mo
Externí odkaz:
http://arxiv.org/abs/2412.05269
In many open environment applications, data are collected in the form of a stream, which exhibits an evolving distribution over time. How to design algorithms to track these evolving data distributions with provable guarantees, particularly in terms
Externí odkaz:
http://arxiv.org/abs/2411.02921
The acquisition of inductive bias through point-level contrastive learning holds paramount significance in point cloud pre-training. However, the square growth in computational requirements with the scale of the point cloud poses a substantial impedi
Externí odkaz:
http://arxiv.org/abs/2410.17207
Recently, multimodal electroencephalogram (EEG) learning has shown great promise in disease detection. At the same time, ensuring privacy in clinical studies has become increasingly crucial due to legal and ethical concerns. One widely adopted scheme
Externí odkaz:
http://arxiv.org/abs/2409.13440
Autor:
Zhu, Qiumin, Sun, Zhen, Xia, Songpengcheng, Liu, Guoqing, Ma, Kehui, Pei, Ling, Gong, Zheng, Jin, Cheng
Traversability estimation in off-road terrains is an essential procedure for autonomous navigation. However, creating reliable labels for complex interactions between the robot and the surface is still a challenging problem in learning-based costmap
Externí odkaz:
http://arxiv.org/abs/2406.08187
In this paper, we develop SE3Set, an SE(3) equivariant hypergraph neural network architecture tailored for advanced molecular representation learning. Hypergraphs are not merely an extension of traditional graphs; they are pivotal for modeling high-o
Externí odkaz:
http://arxiv.org/abs/2405.16511
This work systematically investigates the spin glass behavior of the double perovskite Ca2FeReO6. Building on previous studies, we have developed a formula to quantify the ions distribution at B-site, incorporating the next-nearest neighbor interacti
Externí odkaz:
http://arxiv.org/abs/2404.18748
Fine-tuning pre-trained Large Language Models (LLMs) is essential to align them with human values and intentions. This process often utilizes methods like pairwise comparisons and KL divergence against a reference LLM, focusing on the evaluation of f
Externí odkaz:
http://arxiv.org/abs/2404.11999
Autor:
Xiong, Chaoran, Liu, Guoqing, Wu, Qi, Xia, Songpengcheng, Hua, Tong, Ma, Kehui, Sun, Zhen, Xiang, Yan, Pei, Ling
Temporal misalignment (time offset) between sensors is common in low cost visual-inertial odometry (VIO) systems. Such temporal misalignment introduces inconsistent constraints for state estimation, leading to a significant positioning drift especial
Externí odkaz:
http://arxiv.org/abs/2403.12504
Autor:
Ye, Tianxiang, Wu, Qi, Deng, Junyuan, Liu, Guoqing, Liu, Liu, Xia, Songpengcheng, Pang, Liang, Yu, Wenxian, Pei, Ling
In recent years, Neural Radiance Fields (NeRFs) have demonstrated significant potential in encoding highly-detailed 3D geometry and environmental appearance, positioning themselves as a promising alternative to traditional explicit representation for
Externí odkaz:
http://arxiv.org/abs/2403.10340