Ni Lao
Ni Lao
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Cited by
Cited by
Knowledge vault: A web-scale approach to probabilistic knowledge fusion
X Dong, E Gabrilovich, G Heitz, W Horn, N Lao, K Murphy, T Strohmann, ...
Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014
Never-ending learning
T Mitchell, W Cohen, E Hruschka, P Talukdar, B Yang, J Betteridge, ...
Communications of the ACM 61 (5), 103-115, 2018
Random walk inference and learning in a large scale knowledge base
N Lao, T Mitchell, W Cohen
Proceedings of the 2011 conference on empirical methods in natural language …, 2011
Relational retrieval using a combination of path-constrained random walks
N Lao, WW Cohen
Machine learning 81, 53-67, 2010
Neural symbolic machines: Learning semantic parsers on freebase with weak supervision
C Liang, J Berant, Q Le, KD Forbus, N Lao
ACL 2017, 2016
Automated known problem diagnosis with event traces
C Yuan, N Lao, JR Wen, J Li, Z Zhang, YM Wang, WY Ma
ACM SIGOPS Operating Systems Review 40 (4), 375-388, 2006
Memory augmented policy optimization for program synthesis and semantic parsing
C Liang, M Norouzi, J Berant, QV Le, N Lao
Advances in Neural Information Processing Systems 31, 2018
Rarr: Researching and revising what language models say, using language models
L Gao, Z Dai, P Pasupat, A Chen, AT Chaganty, Y Fan, VY Zhao, N Lao, ...
arXiv preprint arXiv:2210.08726, 2022
Fast query execution for retrieval models based on path-constrained random walks
N Lao, WW Cohen
Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010
Reading the web with learned syntactic-semantic inference rules
N Lao, A Subramanya, F Pereira, W Cohen
Proceedings of the 2012 Joint Conference on Empirical Methods in Natural …, 2012
Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells
G Mai, K Janowicz, B Yan, R Zhu, L Cai, N Lao
ICLR 2020, 2020
A review of location encoding for GeoAI: methods and applications
G Mai, K Janowicz, Y Hu, S Gao, B Yan, R Zhu, L Cai, N Lao
International Journal of Geographical Information Science 36 (4), 639-673, 2022
On the opportunities and challenges of foundation models for geospatial artificial intelligence
G Mai, W Huang, J Sun, S Song, D Mishra, N Liu, S Gao, T Liu, G Cong, ...
arXiv preprint arXiv:2304.06798, 2023
Probabilistic model for contextual retrieval
JR Wen, N Lao, WY Ma
Proceedings of the 27th annual international ACM SIGIR conference on …, 2004
SE‐KGE: A location‐aware Knowledge Graph Embedding model for Geographic Question Answering and Spatial Semantic Lifting
G Mai, K Janowicz, L Cai, R Zhu, B Regalia, B Yan, M Shi, N Lao
Transactions in GIS 24 (3), 623-655, 2020
Efficient inference and learning in a large knowledge base: Reasoning with extracted information using a locally groundable first-order probabilistic logic
WY Wang, K Mazaitis, N Lao, WW Cohen
Machine Learning 100, 101-126, 2015
Towards a foundation model for geospatial artificial intelligence (vision paper)
G Mai, C Cundy, K Choi, Y Hu, N Lao, S Ermon
Proceedings of the 30th International Conference on Advances in Geographic …, 2022
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
J Zhu, N Lao, EP Xing
Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010
Learning relational features with backward random walks
N Lao, E Minkov, W Cohen
Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015
Geographic question answering: challenges, uniqueness, classification, and future directions
G Mai, K Janowicz, R Zhu, L Cai, N Lao
AGILE: GIScience series 2, 8, 2021
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