Követés
Mehran Kazemi
Mehran Kazemi
Senior Research Scientist, Google Research
E-mail megerősítve itt: google.com - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Simple embedding for link prediction in knowledge graphs
SM Kazemi, D Poole
NeurIPS, 2018
8162018
Representation learning for dynamic graphs: A survey
SM Kazemi, R Goel, K Jain, I Kobyzev, A Sethi, P Forsyth, P Poupart
The Journal of Machine Learning Research 21 (1), 2648-2720, 2020
3812020
Time2vec: Learning a vector representation of time
SM Kazemi, R Goel, S Eghbali, J Ramanan, J Sahota, S Thakur, S Wu, ...
arXiv preprint arXiv:1907.05321, 2019
3292019
Diachronic embedding for temporal knowledge graph completion
R Goel, SM Kazemi, M Brubaker, P Poupart
AAAI, 2020
2942020
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
2112023
SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks
B Fatemi, LE Asri, SM Kazemi
NeurIPS, 2021
1102021
RelNN: A deep neural model for relational learning
SM Kazemi, D Poole
AAAI, 2018
652018
Relational Logistic Regression
SM Kazemi, D Buchman, K Kersting, S Natarajan, D Poole
in Proc. 14th International Conference on Principles of Knowledge …, 2014
632014
Relational representation learning for dynamic (knowledge) graphs: A survey
SM Kazemi, R Goel, K Jain, I Kobyzev, A Sethi, P Forsyth, P Poupart
Journal of Machine Learning Research (JMLR) 21 (70), 1-73, 2020
412020
New liftable classes for first-order probabilistic inference
SM Kazemi, A Kimmig, GV Broeck, D Poole
NeurIPS, 2016
402016
LAMBADA: Backward Chaining for Automated Reasoning in Natural Language
SM Kazemi, N Kim, D Bhatia, X Xu, D Ramachandran
ACL, 2023
372023
Out-of-sample representation learning for knowledge graphs
M Albooyeh, R Goel, SM Kazemi
EMNLP, 2020
34*2020
Population size extrapolation in relational probabilistic modelling
D Poole, D Buchman, SM Kazemi, K Kersting, S Natarajan
Scalable Uncertainty Management: 8th International Conference, SUM 2014 …, 2014
342014
Knowledge compilation for lifted probabilistic inference: Compiling to a low-level language
SM Kazemi, D Poole
Fifteenth International Conference on the Principles of Knowledge …, 2016
19*2016
Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples
A Saparov, RY Pang, V Padmakumar, N Joshi, SM Kazemi, N Kim, H He
NeurIPS, 2023
182023
Structure learning for relational logistic regression: an ensemble approach
N Ramanan, G Kunapuli, T Khot, B Fatemi, SM Kazemi, D Poole, ...
Data Mining and Knowledge Discovery 35, 2089-2111, 2021
162021
Dr. ICL: Demonstration-Retrieved In-context Learning
M Luo, X Xu, Z Dai, P Pasupat, M Kazemi, C Baral, V Imbrasaite, VY Zhao
FoMo Workshop, 2023
132023
Bridging weighted rules and graph random walks for statistical relational models
SM Kazemi, D Poole
Frontiers in Robotics and AI 5, 8, 2018
132018
Relational Logistic Regression: The Directed Analog of Markov Logic Networks.
SM Kazemi, D Buchman, K Kersting, S Natarajan, D Poole
AAAI Workshop: Statistical Relational Artificial Intelligence, 2014
132014
A learning algorithm for relational logistic regression: Preliminary results
B Fatemi, SM Kazemi, D Poole
Statistical Relational AI Workshop, 2016
122016
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Cikkek 1–20