Research and Development

Recurrent Neural Networks


Efficient Simulation of Finite Automata by Neural Nets by Noga Alon, A. K. Dewdney and Teunis J. Ott, Learning the Structure of Event Sequences by Axel Cleeremans and James L. McClelland, Recurrent Neural Networks and Finite Automata by Hava T. Siegelmann, A Comparative Study of Recurrent Neural Network Architectures on Learning Temporal Sequences by Tung-Bo Chen and Von-Wun Soo, Long Short-term Memory by Sepp Hochreiter and Jürgen Schmidhuber and Recurrent Neural Networks: Design and Applications edited by Larry Medsker and Lakhmi C. Jain.

Time Series

Recurrent Neural Networks for Time Series Classification by Michael Hüsken and Peter Stagge and Time-series Event Prediction with Evolutionary State Graph by Wenjie Hu, Yang Yang, Ziqiang Cheng, Carl Yang and Xiang Ren.


Event2vec: Learning Representations of Events on Temporal Sequences by Shenda Hong, Meng Wu, Hongyan Li and Zhengwu Wu, Event2vec: Neural Embeddings for News Events by Vinay Setty and Katja Hose and Event Representations for Automated Story Generation with Deep Neural Nets by Lara Martin, Prithviraj Ammanabrolu, Xinyu Wang, William Hancock, Shruti Singh, Brent Harrison and Mark O. Riedl.


Hebbian Learning of Context in Recurrent Neural Networks by Nicolas Brunel.


E-RNN: Entangled Recurrent Neural Networks for Causal Prediction by Jinsung Yoon and Mihaela van der Schaar, Improving Event Causality Identification via Self-supervised Representation Learning on External Causal Statement by Xinyu Zuo, Pengfei Cao, Yubo Chen, Kang Liu, Jun Zhao, Weihua Peng and Yuguang Chen and Exploiting Rich Event Representation to Improve Event Causality Recognition by Gaigai Jin, Junsheng Zhou, Weiguang Qu, Yunfei Long and Yanhui Gu.


Abstracting Causal Models by Sander Beckers and Joseph Y. Halpern, Event Abstraction in Process Mining: Literature Review and Taxonomy by Sebastiaan J. van Zelst, Felix Mannhardt, Massimiliano de Leoni and Agnes Koschmider, Semantic Causal Abstraction for Event Prediction by Sasha Strelnikoff, Aruna Jammalamadaka and Tsai-Ching Lu and Abstraction between Structural Causal Models: A Review of Definitions and Properties by Fabio M. Zennaro.


Classifying Process Instances Using Recurrent Neural Networks by Markku Hinkka, Teemu Lehto, Keijo Heljanko and Alexander Jung, A Graph-based Approach to Interpreting Recurrent Neural Networks in Process Mining by Khadijah M. Hanga, Yevgeniya Kovalchuk and Mohamed M. Gaber and Learning of Process Representations Using Recurrent Neural Networks by Alexander Seeliger, Stefan Luettgen, Timo Nolle and Max Mühlhäuser.


Inducing Neural Models of Script Knowledge by Ashutosh Modi and Ivan Titov, Event Embeddings for Semantic Script Modeling by Ashutosh Modi and Integrating Order Information and Event Relation for Script Event Prediction by Zhongqing Wang, Yue Zhang and Ching Y. Chang.


Unsupervised Learning of Narrative Event Chains by Nathanael Chambers and Dan Jurafsky and Modelling Protagonist Goals and Desires in First-person Narrative by Elahe Rahimtoroghi, Jiaqi Wu, Ruimin Wang, Pranav Anand and Marilyn A. Walker.

Plan, Activity and Intent Recognition

Using a Recursive Neural Network to Learn an Agent's Decision Model for Plan Recognition by Francis Bisson, Hugo Larochelle and Froduald Kabanza, Differential Recurrent Neural Networks for Action Recognition by Vivek Veeriah, Naifan Zhuang and Guo-Jun Qi, Human Activity Recognition Using Recurrent Neural Networks by Deepika Singh, Erinc Merdivan, Ismini Psychoula, Johannes Kropf, Sten Hanke, Matthieu Geist and Andreas Holzinger and Deep Recurrent Neural Networks for Human Activity Recognition by Abdulmajid Murad and Jae-Young Pyun.

Recommender Systems

Contextual Sequence Modeling for Recommendation with Recurrent Neural Networks by Elena Smirnova and Flavian Vasile, Deep Learning Based Recommender System: A Survey and New Perspectives by Shuai Zhang, Lina Yao, Aixin Sun and Yi Tay, Temporal-contextual Recommendation in Real-time by Yifei Ma, Balakrishnan Narayanaswamy, Haibin Lin and Hao Ding, A Survey on Session-based Recommender Systems by Shoujin Wang, Longbing Cao, Yan Wang, Quan Z. Sheng, Mehmet A. Orgun and Defu Lian, Session-based Recommender Systems by Dietmar Jannach, Massimo Quadrana and Paolo Cremonesi, Learning Path Recommender System based on Recurrent Neural Network by Tomohiro Saito and Yutaka Watanobe and Recurrent Neural Networks for Recommender Systems by Ankit Rath and Subhrajyoti R. Sahu.

Intelligent Tutoring Systems

On the Use of Neural Networks in Intelligent Tutoring Systems by Susan A. Mengel and William Lively, Using Neural Networks to Predict Student Behavior in Intelligent Tutoring Systems by Susan A. Mengel and Applications of Neural Networks to Intelligent Tutoring Systems by Chlotia L. Posey.