Incorporation of Deep Neural Network & Reinforcement Learning with Domain Knowledge

29 July 2021

Papers citing "Incorporation of Deep Neural Network & Reinforcement Learning with Domain Knowledge"

22 / 22 papers shown

Title
Incorporating Symbolic Domain Knowledge into Graph Neural Networks T. Dash A. Srinivasan Lovekesh Vig NAI 85 25 0 23 Oct 2020
Propositionalization and Embeddings: Two Sides of the Same Coin Nada Lavrac Blaž Škrlj Marko Robnik-Šikonja 93 26 0 08 Jun 2020
Turning 30: New Ideas in Inductive Logic Programming Andrew Cropper Sebastijan Dumancic Stephen Muggleton LRM AI4CE 72 83 0 25 Feb 2020
Knowledge Infused Learning (K-IL): Towards Deep Incorporation of Knowledge in Deep Learning Ugur Kursuncu Manas Gaur A. Sheth NAI 58 58 0 01 Dec 2019
A Comprehensive Survey on Transfer Learning Fuzhen Zhuang Zhiyuan Qi Keyu Duan Dongbo Xi Yongchun Zhu Hengshu Zhu Hui Xiong Qing He 177 4,428 0 07 Nov 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 116 6,251 0 22 Oct 2019
Towards Knowledge-Based Recommender Dialog System Qibin Chen Junyang Lin Yichang Zhang Ming Ding Yukuo Cen Hongxia Yang Jie Tang 51 239 0 15 Aug 2019
Neural Probabilistic Logic Programming in DeepProbLog Robin Manhaeve Sebastijan Dumancic Angelika Kimmig T. Demeester Luc de Raedt NAI 80 555 0 18 Jul 2019
Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks Namyong Park Andrey Kan Xin Luna Dong Tong Zhao Christos Faloutsos 52 158 0 21 May 2019
Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems Laura von Rueden S. Mayer Katharina Beckh B. Georgiev Sven Giesselbach ... Rajkumar Ramamurthy Michal Walczak Jochen Garcke Christian Bauckhage Jannis Schuecker 53 638 0 29 Mar 2019
Knowledge Graph Convolutional Networks for Recommender Systems Hongwei Wang Miao Zhao Xing Xie Wenjie Li Minyi Guo 63 929 0 18 Mar 2019
Improving the Interpretability of Deep Neural Networks with Knowledge Distillation Xuan Liu Xiaoguang Wang Stan Matwin HAI 46 98 0 28 Dec 2018
Logical Explanations for Deep Relational Machines Using Relevance Information A. Srinivasan Lovekesh Vig Michael Bain FAtt 27 15 0 02 Jul 2018
Imitating Latent Policies from Observation Ashley D. Edwards Himanshu Sahni Yannick Schroecker Charles Isbell 68 137 0 21 May 2018
A Semantic Loss Function for Deep Learning with Symbolic Knowledge Jingyi Xu Zilu Zhang Tal Friedman Yitao Liang Guy Van den Broeck 82 450 0 29 Nov 2017
Learning Explanatory Rules from Noisy Data Richard Evans Edward Grefenstette 111 483 0 13 Nov 2017
Neural-Symbolic Learning and Reasoning: A Survey and Interpretation Tarek R. Besold Artur Garcez Sebastian Bader Howard L. Bowman Pedro M. Domingos ... P. Lima L. Penning Gadi Pinkas Hoifung Poon Gerson Zaverucha LRM AI4CE 68 343 0 10 Nov 2017
Regularization for Deep Learning: A Taxonomy J. Kukačka Vladimir Golkov Daniel Cremers 80 335 0 29 Oct 2017
The Mythos of Model Interpretability Zachary Chase Lipton FaML 172 3,685 0 10 Jun 2016
Harnessing Deep Neural Networks with Logic Rules Zhiting Hu Xuezhe Ma Zhengzhong Liu Eduard H. Hovy Eric Xing AI4CE NAI 48 613 0 21 Mar 2016
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 327 19,609 0 09 Mar 2015
How transferable are features in deep neural networks? J. Yosinski Jeff Clune Yoshua Bengio Hod Lipson OOD 212 8,330 0 06 Nov 2014