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We present a survey of ways in which existing scientific knowledge are included when constructing models with neural networks.
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Deep relational machines
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Fast relational learning using bottom clause propositionalization with artificial neural networks
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Low-dimensional embeddings of logic
Rocktäschel, T., Bosnjak, M., Singh, S. & Riedel, S · 2014
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klog: A language for logical and relational learning with kernels
Frasconi, P., Costa, F., De Raedt, L. & De Grave, K · 2014
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Injecting logical background knowledge into embeddings for relation extraction
Rocktäschel, T., Singh, S. & Riedel, S · 2015
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Distilling the knowledge in a neural network
Hinton, G., Vinyals, O. & Dean, J · 2015
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Simultaneous deep transfer across domains and tasks
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Artificial intelligence to win the nobel prize and beyond: Creating the engine for scientific discovery
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The mythos of model interpretability
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Jointly embedding knowledge graphs and logical rules
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Lifted rule injection for relation embeddings
Demeester, T., Rocktäschel, T. & Riedel, S · 2016
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Harnessing deep neural networks with logic rules
Hu, Z., Ma, X., Liu, Z., Hovy, E. & Xing, E · 2016
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Logic tensor networks: Deep learning and logical reasoning from data and knowledge
Serafini, L. & Garcez, A. d · 2016
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An investigation into the role of domain-knowledge on the use of embeddings
Vig, L., Srinivasan, A., Bain, M. & Verma, A · 2017
Embedding symbolic knowledge into deep networks
Xie, Y., Xu, Z., Kankanhalli, M. S., Meel, K. S. & Soh, H · 2019
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The global landscape of ai ethics guidelines
Jobin, A., Ienca, M. & Vayena, E · 2019
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Srinivasan, A., Vig, L. & Bain, M · 2019
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Ai for science
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Ai for social good: unlocking the opportunity for positive impact
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From statistical relational to neuro-symbolic artificial intelligence
Raedt, L. d., Dumančić, S., Manhaeve, R. & Marra, G · 2020
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Semantic-based regularization for learning and inference
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Integrating prior knowledge into deep learning
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Attention is all you need
Vaswani, A. et al · 2017
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Ellis, K., Morales, L., Meyer, M. S., Solar-Lezama, A. & Tenenbaum, J. B · 2018
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Turning 30: New ideas in inductive logic programming
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Knowledge graphs to empower humanity-inspired ai systems
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Hogan, A. et al · 2020
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Injecting domain knowledge in neural networks: a controlled experiment on a constrained problem
Silvestri, M., Lombardi, M. & Milano, M · 2020
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A comprehensive survey on transfer learning
Zhuang, F. et al · 2020
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Adversarial and domain-aware bert for cross-domain sentiment analysis
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Neural unsupervised domain adaptation in nlp—a survey
Ramponi, A. & Plank, B · 2020
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Beyond graph neural networks with lifted relational neural networks
Sourek, G., Zelezny, F. & Kuzelka, O · 2020
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Riegel, R. et al · 2020
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Tensorlog: A probabilistic database implemented using deep-learning infrastructure
Cohen, W., Yang, F. & Mazaitis, K. R · 2020
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Language models are few-shot learners
Brown, T. B. et al · 2020
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Incorporating symbolic domain knowledge into graph neural networks
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Informed machine learning-a taxonomy and survey of integrating prior knowledge into learning systems
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Generative adversarial network-based transfer reinforcement learning for routing with prior knowledge
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