Cikkek nyilvánosan hozzáférhető megbízással - Le SongTovábbi információ
Sehol sem hozzáférhető: 2
Concentric spherical neural network for 3d representation learning
J Fox, B Zhao, BG Del Rio, S Rajamanickam, R Ramprasad, L Song
2022 international joint conference on neural networks (IJCNN), 1-8, 2022
Megbízások: US National Science Foundation, US Department of Energy
On the Number of Linear Regions of Convolutional Neural Networks With Piecewise Linear Activations
H Xiong, L Huang, WJT Zang, X Zhen, GS Xie, B Gu, L Song
IEEE Transactions on Pattern Analysis and Machine Intelligence 46 (7), 5131-5148, 2024
Megbízások: National Natural Science Foundation of China
Valahol hozzáférhető: 117
Sphereface: Deep hypersphere embedding for face recognition
W Liu, Y Wen, Z Yu, M Li, B Raj, L Song
Proceedings of the IEEE conference on computer vision and pattern …, 2017
Megbízások: National Natural Science Foundation of China
Learning combinatorial optimization algorithms over graphs
E Khalil, H Dai, Y Zhang, B Dilkina, L Song
Advances in neural information processing systems 30, 2017
Megbízások: US National Science Foundation, US Department of Defense, US National …
Scientific discovery in the age of artificial intelligence
H Wang, T Fu, Y Du, W Gao, K Huang, Z Liu, P Chandak, S Liu, ...
Nature 620 (7972), 47-60, 2023
Megbízások: US Department of Defense, US National Institutes of Health
Adversarial attack on graph structured data
H Dai, H Li, T Tian, X Huang, L Wang, J Zhu, L Song
International conference on machine learning, 1115-1124, 2018
Megbízások: US National Science Foundation, US Department of Defense, US National …
Discriminative embeddings of latent variable models for structured data
H Dai, B Dai, L Song
International conference on machine learning, 2702-2711, 2016
Megbízások: US National Science Foundation, US National Institutes of Health
GRAM: graph-based attention model for healthcare representation learning
E Choi, MT Bahadori, L Song, WF Stewart, J Sun
Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017
Megbízások: US National Science Foundation, US Department of Defense, US National …
Recurrent marked temporal point processes: Embedding event history to vector
N Du, H Dai, R Trivedi, U Upadhyay, M Gomez-Rodriguez, L Song
Proceedings of the 22nd ACM SIGKDD international conference on knowledge …, 2016
Megbízások: US National Science Foundation, US National Institutes of Health
Neural network-based graph embedding for cross-platform binary code similarity detection
X Xu, C Liu, Q Feng, H Yin, L Song, D Song
Proceedings of the 2017 ACM SIGSAC conference on computer and communications …, 2017
Megbízások: US National Science Foundation, US Department of Defense
Learning to explain: An information-theoretic perspective on model interpretation
J Chen, L Song, M Wainwright, M Jordan
International conference on machine learning, 883-892, 2018
Megbízások: US National Science Foundation, US Department of Defense, US National …
Know-evolve: Deep temporal reasoning for dynamic knowledge graphs
R Trivedi, H Dai, Y Wang, L Song
international conference on machine learning, 3462-3471, 2017
Megbízások: US National Science Foundation, US Department of Defense, US National …
Variational reasoning for question answering with knowledge graph
Y Zhang, H Dai, Z Kozareva, A Smola, L Song
Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018
Megbízások: US National Science Foundation, US Department of Defense, US National …
Learning to branch in mixed integer programming
E Khalil, P Le Bodic, L Song, G Nemhauser, B Dilkina
Proceedings of the AAAI conference on artificial intelligence 30 (1), 2016
Megbízások: US National Science Foundation, US National Institutes of Health
Iterative learning with open-set noisy labels
Y Wang, W Liu, X Ma, J Bailey, H Zha, L Song, ST Xia
Proceedings of the IEEE conference on computer vision and pattern …, 2018
Megbízások: US National Science Foundation, US Department of Defense, National Natural …
Material structure-property linkages using three-dimensional convolutional neural networks
A Cecen, H Dai, YC Yabansu, SR Kalidindi, L Song
Acta Materialia 146, 76-84, 2018
Megbízások: US National Science Foundation, US Department of Defense, US National …
SBEED: Convergent reinforcement learning with nonlinear function approximation
B Dai, A Shaw, L Li, L Xiao, N He, Z Liu, J Chen, L Song
International conference on machine learning, 1125-1134, 2018
Megbízások: US National Science Foundation, US Department of Defense, US National …
Scalable influence estimation in continuous-time diffusion networks
N Du, L Song, M Gomez Rodriguez, H Zha
Advances in neural information processing systems 26, 2013
Megbízások: US National Institutes of Health
Coevolve: A joint point process model for information diffusion and network evolution
M Farajtabar, Y Wang, M Gomez-Rodriguez, S Li, H Zha, L Song
Journal of Machine Learning Research 18 (41), 1-49, 2017
Megbízások: US National Science Foundation, US Department of Defense, US National …
Emerging materials intelligence ecosystems propelled by machine learning
R Batra, L Song, R Ramprasad
Nature Reviews Materials 6 (8), 655-678, 2021
Megbízások: US National Science Foundation, US Department of Energy, US Department of …
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