Publications

Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani, Dmitrii Khizbullin, Bernard Ghanem (2023). CAMEL: Communicative Agents for ''Mind'' Exploration of Large Language Model Society. NeurIPS’2023.

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Guohao Li, Chenxin Xiong, Guocheng Qian, Ali Thabet, Bernard Ghanem (2023). DeeperGCN: Training Deeper GCNs with Generalized Aggregation Functions. TPAMI’2023.

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Junting Chen, Guohao Li, Suryansh Kumar, Bernard Ghanem, Fisher Yu (2023). How To Not Train Your Dragon: Training-free Embodied Object Goal Navigation with Semantic Frontiers. RSS’2023.

Weijiang Yu, Haofan Wang, Guohao Li, Nong Xiao, Bernard Ghanem (2023). Knowledge-aware Global Reasoning for Situation Recognition. TPAMI’2023.

Guohao Li, Mengmeng Xu, Silvio Giancola, Ali Thabet, Bernard Ghanem (2022). LC-NAS: Latency constrained neural architecture search for point cloud networks. 3DV’2022.

Kezhi Kong, Guohao Li, Mucong Ding, Zuxuan Wu, Chen Zhu, Bernard Ghanem, Gavin Taylor, Tom Goldstein (2022). Robust Optimization as Data Augmentation for Large-scale Graphs. CVPR’2022.

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Guocheng Qian, Hasan Abed Al Kader Hammoud, Guohao Li, Ali Thabet, Bernard Ghanem (2021). ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning. NeurIPS’2021 Spotlight.

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Guohao Li, Matthias Müller, Bernard Ghanem, Vladlen Koltun (2021). Training Graph Neural Networks with 1000 layers. ICML’2021.

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Guohao Li, Matthias Müller, Guocheng Qian, Itzel C. Delgadillo, Abdulellah Abualshour, Ali Thabet, Bernard Ghanem (2021). DeepGCNs: Making GCNs Go as Deep as CNNs. TPAMI’2021.

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Guocheng Qian, Abdulellah Abualshour, Guohao Li, Ali Thabet, Bernard Ghanem (2021). PU-GCN: Point Cloud Upsampling via Graph Convolutional Network. CVPR’2021.

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Guohao Li, Guocheng Qian, Itzel C. Delgadillo, Matthias Müller, Ali Thabet, Bernard Ghanem (2019). SGAS: Sequential Greedy Architecture Search. CVPR’2020.

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Guohao Li, Matthias Müller, Ali Thabet, Bernard Ghanem (2019). DeepGCNs: Can GCNs Go as Deep as CNNs?. ICCV’2019 Oral.

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Guohao Li, Matthias Müller, Vincent Casser, Neil Smith, Dominik L. Michels, Bernard Ghanem (2018). OIL: Observational Imitation Learning. RSS’2019.

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