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Deep Learning for Predictive Business Process Monitoring: Review and Benchmark

24 September 2020

Papers citing "Deep Learning for Predictive Business Process Monitoring: Review and Benchmark"

36 / 36 papers shown

Title
Process Outcome Prediction: CNN vs. LSTM (with Attention) Hans Weytjens Jochen De Weerdt AI4TS 57 44 0 14 Apr 2021
A systematic literature review on state-of-the-art deep learning methods for process prediction Dominic A. Neu Johannes Lahann Peter Fettke AI4CE 62 132 0 22 Jan 2021
Multi-Task Learning with Deep Neural Networks: A Survey M. Crawshaw CVBM 217 625 0 10 Sep 2020
The Curious Case of Neural Text Degeneration Ari Holtzman Jan Buys Li Du Maxwell Forbes Yejin Choi 199 3,210 0 22 Apr 2019
Exploiting Event Log Event Attributes in RNN Based Prediction Markku Hinkka Teemu Lehto Keijo Heljanko 42 28 0 15 Apr 2019
An Interdisciplinary Comparison of Sequence Modeling Methods for Next-Element Prediction Niek Tax Irene Teinemaa S. V. Zelst 36 61 0 31 Oct 2018
Classifying Process Instances Using Recurrent Neural Networks Markku Hinkka Teemu Lehto Keijo Heljanko Alexander Jung 39 38 0 16 Sep 2018
Hierarchical Neural Story Generation Angela Fan M. Lewis Yann N. Dauphin DiffM 183 1,626 0 13 May 2018
Survey and cross-benchmark comparison of remaining time prediction methods in business process monitoring I. Verenich Marlon Dumas M. Rosa F. Maggi Irene Teinemaa AI4TS 56 155 0 08 May 2018
Predictive Process Monitoring Methods: Which One Suits Me Best? Chiara Di Francescomarino Chiara Ghidini F. Maggi Fredrik P. Milani 36 146 0 06 Apr 2018
Deep contextualized word representations Matthew E. Peters Mark Neumann Mohit Iyyer Matt Gardner Christopher Clark Kenton Lee Luke Zettlemoyer NAI 233 11,566 0 15 Feb 2018
LSTM Networks for Data-Aware Remaining Time Prediction of Business Process Instances Nicoló Navarin B. Vincenzi Mirko Polato A. Sperduti AI4TS 42 91 0 10 Nov 2017
Outcome-Oriented Predictive Process Monitoring: Review and Benchmark Irene Teinemaa Marlon Dumas M. Rosa F. Maggi 40 186 0 21 Jul 2017
An Overview of Multi-Task Learning in Deep Neural Networks Sebastian Ruder CVBM 159 2,831 0 15 Jun 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 299 5,862 0 14 Jun 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 786 132,363 0 12 Jun 2017
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics Alex Kendall Y. Gal R. Cipolla 3DH 272 3,135 0 19 May 2017
XES Tensorflow - Process Prediction using the Tensorflow Deep-Learning Framework Joerg Evermann Jana-Rebecca Rehse Peter Fettke 45 13 0 03 May 2017
Comparative Study of CNN and RNN for Natural Language Processing Wenpeng Yin Katharina Kann Mo Yu Hinrich Schütze 79 992 0 07 Feb 2017
Predicting Process Behaviour using Deep Learning Joerg Evermann Jana-Rebecca Rehse Peter Fettke 69 358 0 14 Dec 2016
Predictive Business Process Monitoring with LSTM Neural Networks Niek Tax I. Verenich M. Rosa Marlon Dumas 54 450 0 07 Dec 2016
Statistical comparison of classifiers through Bayesian hierarchical modelling Giorgio Corani A. Benavoli J. Demšar Francesca Mangili Marco Zaffalon 41 55 0 28 Sep 2016
Time for a change: a tutorial for comparing multiple classifiers through Bayesian analysis A. Benavoli Giorgio Corani J. Demšar Marco Zaffalon BDL 67 424 0 14 Jun 2016
One-shot Learning with Memory-Augmented Neural Networks Adam Santoro Sergey Bartunov M. Botvinick Daan Wierstra Timothy Lillicrap 79 525 0 19 May 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,426 0 10 Dec 2015
Effective Approaches to Attention-based Neural Machine Translation Thang Luong Hieu H. Pham Christopher D. Manning 413 7,969 0 17 Aug 2015
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling Junyoung Chung Çağlar Gülçehre Kyunghyun Cho Yoshua Bengio 601 12,741 0 11 Dec 2014
Neural Turing Machines Alex Graves Greg Wayne Ivo Danihelka 108 2,331 0 20 Oct 2014
Going Deeper with Convolutions Christian Szegedy Wei Liu Yangqing Jia P. Sermanet Scott E. Reed Dragomir Anguelov D. Erhan Vincent Vanhoucke Andrew Rabinovich 488 43,694 0 17 Sep 2014
Sequence to Sequence Learning with Neural Networks Ilya Sutskever Oriol Vinyals Quoc V. Le AIMat 446 20,590 0 10 Sep 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,508 0 04 Sep 2014
Neural Machine Translation by Jointly Learning to Align and Translate Dzmitry Bahdanau Kyunghyun Cho Yoshua Bengio AIMat 578 27,327 0 01 Sep 2014
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation Kyunghyun Cho B. V. Merrienboer Çağlar Gülçehre Dzmitry Bahdanau Fethi Bougares Holger Schwenk Yoshua Bengio AIMat 1.1K 23,388 0 03 Jun 2014
Efficient Estimation of Word Representations in Vector Space Tomas Mikolov Kai Chen G. Corrado J. Dean 3DV 684 31,544 0 16 Jan 2013
What Regularized Auto-Encoders Learn from the Data Generating Distribution Guillaume Alain Yoshua Bengio OOD DRL 72 505 0 18 Nov 2012
Feature Hashing for Large Scale Multitask Learning Kilian Q. Weinberger A. Dasgupta Josh Attenberg John Langford Alex Smola 119 1,023 0 12 Feb 2009