%%% General Books and Citations

%beam search
@inproceedings{graves2013speech,
  title={Speech recognition with deep recurrent neural networks},
  author={Graves, Alex and Mohamed, Abdel-rahman and Hinton, Geoffrey},
  booktitle={Acoustics, speech and signal processing (icassp), 2013 ieee international conference on},
  pages={6645--6649},
  year={2013},
  organization={IEEE}
}

%Fully connected NN
@article{gent1992special,
  title={Special Feature. Predicting time series by a fully connected neural network trained by back propagation},
  author={Gent, CR and Sheppard, CP},
  journal={Computing \& Control Engineering Journal},
  volume={3},
  number={3},
  pages={109--112},
  year={1992},
  publisher={IET}
}

%Geant4
@article{agostinelli2003s,
  title={S. Agostinelli et al.(GEANT4 Collaboration), Nucl. Instrum. Methods Phys. Res., Sect. A 506, 250 (2003).},
  author={Agostinelli, S},
  journal={Nucl. Instrum. Methods Phys. Res., Sect. A},
  volume={506},
  pages={250},
  year={2003}
}

%sklearn
@article{pedregosa2011scikit,
  title={Scikit-learn: Machine learning in Python},
  author={Pedregosa, Fabian and Varoquaux, Ga{\"e}l and Gramfort, Alexandre and Michel, Vincent and Thirion, Bertrand and Grisel, Olivier and Blondel, Mathieu and Prettenhofer, Peter and Weiss, Ron and Dubourg, Vincent and others},
  journal={Journal of machine learning research},
  volume={12},
  number={Oct},
  pages={2825--2830},
  year={2011}
}

%Thomson book
@book{thomson2013modern,
  title={Modern particle physics},
  author={Thomson, Mark},
  year={2013},
  publisher={Cambridge University Press}
}

%Neutrino mixing angle measruements KamLAND
@article{abe2008precision,
  title={Precision measurement of neutrino oscillation parameters with KamLAND},
  author={Abe, S and Ebihara, T and Enomoto, S and Furuno, K and Gando, Y and Ichimura, K and Ikeda, H and Inoue, K and Kibe, Y and Kishimoto, Y and others},
  journal={Physical Review Letters},
  volume={100},
  number={22},
  pages={221803},
  year={2008},
  publisher={APS}
}

%Neutrino mixing angle measruements MINOS
@article{adamson2011measurement,
  title={Measurement of the neutrino mass splitting and flavor mixing by MINOS},
  author={Adamson, P and Andreopoulos, C and Armstrong, R and Auty, DJ and Ayres, DS and Backhouse, C and Barr, G and Bishai, M and Blake, A and Bock, GJ and others},
  journal={Physical Review Letters},
  volume={106},
  number={18},
  pages={181801},
  year={2011},
  publisher={APS}
}

%mu to eee paper
@article{blondel2013research,
  title={Research Proposal for an Experiment to Search for the Decay $\mu \rightarrow eee$},
  author={Blondel, A and Bravar, A and Pohl, M and Bachmann, S and Berger, N and Kiehn, M and Sch{\"o}ning, A and Wiedner, D and Windelband, B and Eckert, P and others},
  journal={arXiv preprint arXiv:1301.6113},
  year={2013}
}

%GRU
@article{chung2014empirical,
  title={Empirical evaluation of gated recurrent neural networks on sequence modeling},
  author={Chung, Junyoung and Gulcehre, Caglar and Cho, KyungHyun and Bengio, Yoshua},
  journal={arXiv preprint arXiv:1412.3555},
  year={2014}
}

%LSTM
@article{gers1999learning,
  title={Learning to forget: Continual prediction with LSTM},
  author={Gers, Felix A and Schmidhuber, J{\"u}rgen and Cummins, Fred},
  year={1999},
  publisher={IET}
}

%ROC curve
@article{ML:ROC_AUC:Bradley:1997:UAU:1746432.1746434,
 author = {Bradley, Andrew P.},
 title = {The Use of the Area Under the ROC Curve in the Evaluation of Machine Learning Algorithms},
 journal = {Pattern Recogn.},
 issue_date = {July, 1997},
 volume = {30},
 number = {7},
 month = jul,
 year = {1997},
 issn = {0031-3203},
 pages = {1145--1159},
 numpages = {15},
 url = {http://dx.doi.org/10.1016/S0031-3203(96)00142-2},
 doi = {10.1016/S0031-3203(96)00142-2},
 acmid = {1746434},
 publisher = {Elsevier Science Inc.},
 address = {New York, NY, USA},
 keywords = {Accuracy measures, Cross-validation, Standard error, The ROC curve, The area under the ROC curve (AUC), Wilcoxon statistic},
}

%XGBoost
@article{ML:XGBoost,
  author    = {Tianqi Chen and
               Carlos Guestrin},
  title     = {XGBoost: {A} Scalable Tree Boosting System},
  journal   = {CoRR},
  volume    = {abs/1603.02754},
  year      = {2016},
  url       = {http://arxiv.org/abs/1603.02754},
  timestamp = {Sat, 02 Apr 2016 11:49:48 +0200},
  biburl    = {http://dblp.uni-trier.de/rec/bib/journals/corr/ChenG16},
  bibsource = {dblp computer science bibliography, http://dblp.org}
}

%Selu and other activation functions
@inproceedings{klambauer2017self,
  title={Self-normalizing neural networks},
  author={Klambauer, G{\"u}nter and Unterthiner, Thomas and Mayr, Andreas and Hochreiter, Sepp},
  booktitle={Advances in Neural Information Processing Systems},
  pages={971--980},
  year={2017}
}

%Mupix detector
@article{augustin2017mupix,
  title={The MuPix system-on-chip for the Mu3e experiment},
  author={Augustin, Heiko and Berger, Niklaus and Dittmeier, Sebastian and Grzesik, Carsten and Hammerich, Jan and Huang, Qinhua and Huth, Lennart and Kiehn, Moritz and Kozlinskiy, Alexandr and Aeschbacher, Frank Meier and others},
  journal={Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment},
  volume={845},
  pages={194--198},
  year={2017},
  publisher={Elsevier}
}

@techreport{philipp2015hv,
  title={Das HV-MAPS basierte MuPix Teleskop},
  author={Philipp, Jonathan and Huth, Lennart and Augustin, Heiko and Philipp, Raphael and Wiedner, Dirk and Berger, Niklaus and Mu3e Collaboration and others},
  year={2015},
  institution={Detector RD at DESY Test beam}
}

@article{augustin2015mupix,
  title={The MuPix high voltage monolithic active pixel sensor for the Mu3e experiment},
  author={Augustin, Heiko and Berger, N and Bravar, S and Corrodi, Simon and Damyanova, A and F{\"o}rster, F and Gredig, R and Herkert, A and Huang, Q and Huth, L and others},
  journal={Journal of Instrumentation},
  volume={10},
  number={03},
  pages={C03044},
  year={2015},
  publisher={IOP Publishing}
}

%Keras
@article{chollet2015keras,
  title={Keras: Deep learning library for theano and tensorflow},
  author={Chollet, Fran{\c{c}}ois and others},
  journal={URL: https://keras. io/k},
  volume={7},
  number={8},
  year={2015}
}

%Tensorflow
@inproceedings{abadi2016tensorflow,
  title={Tensorflow: a system for large-scale machine learning.},
  author={Abadi, Mart{\'\i}n and Barham, Paul and Chen, Jianmin and Chen, Zhifeng and Davis, Andy and Dean, Jeffrey and Devin, Matthieu and Ghemawat, Sanjay and Irving, Geoffrey and Isard, Michael and others},
  booktitle={OSDI},
  volume={16},
  pages={265--283},
  year={2016}
}

%Batchnorm in between layers
@article{cooijmans2016recurrent,
  title={Recurrent batch normalization},
  author={Cooijmans, Tim and Ballas, Nicolas and Laurent, C{\'e}sar and G{\"u}l{\c{c}}ehre, {\c{C}}a{\u{g}}lar and Courville, Aaron},
  journal={arXiv preprint arXiv:1603.09025},
  year={2016}
}

@article{ioffe2015batch,
  title={Batch normalization: Accelerating deep network training by reducing internal covariate shift},
  author={Ioffe, Sergey and Szegedy, Christian},
  journal={arXiv preprint arXiv:1502.03167},
  year={2015}
}

%XGBoost
@inproceedings{chen2016xgboost,
  title={Xgboost: A scalable tree boosting system},
  author={Chen, Tianqi and Guestrin, Carlos},
  booktitle={Proceedings of the 22nd acm sigkdd international conference on knowledge discovery and data mining},
  pages={785--794},
  year={2016},
  organization={ACM}
}

%ROC curve
@article{ML:ROC_AUC:Bradley:1997:UAU:1746432.1746434,
 author = {Bradley, Andrew P.},
 title = {The Use of the Area Under the ROC Curve in the Evaluation of Machine Learning Algorithms},
 journal = {Pattern Recogn.},
 issue_date = {July, 1997},
 volume = {30},
 number = {7},
 month = jul,
 year = {1997},
 issn = {0031-3203},
 pages = {1145--1159},
 numpages = {15},
 url = {http://dx.doi.org/10.1016/S0031-3203(96)00142-2},
 doi = {10.1016/S0031-3203(96)00142-2},
 acmid = {1746434},
 publisher = {Elsevier Science Inc.},
 address = {New York, NY, USA},
 keywords = {Accuracy measures, Cross-validation, Standard error, The ROC curve, The area under the ROC curve (AUC), Wilcoxon statistic},
}

%RNN
@article{grossberg2013recurrent,
  title={Recurrent neural networks},
  author={Grossberg, Stephen},
  journal={Scholarpedia},
  volume={8},
  number={2},
  pages={1888},
  year={2013}
}

@article{connor1994recurrent,
  title={Recurrent neural networks and robust time series prediction},
  author={Connor, Jerome T and Martin, R Douglas and Atlas, Les E},
  journal={IEEE transactions on neural networks},
  volume={5},
  number={2},
  pages={240--254},
  year={1994},
  publisher={IEEE}
}

%Adam
@inproceedings{chilimbi2014project,
  title={Project Adam: Building an Efficient and Scalable Deep Learning Training System.},
  author={Chilimbi, Trishul M and Suzue, Yutaka and Apacible, Johnson and Kalyanaraman, Karthik},
  booktitle={OSDI},
  volume={14},
  pages={571--582},
  year={2014}
}

%Bidirectional RNN
@article{schuster1997bidirectional,
  title={Bidirectional recurrent neural networks},
  author={Schuster, Mike and Paliwal, Kuldip K},
  journal={IEEE Transactions on Signal Processing},
  volume={45},
  number={11},
  pages={2673--2681},
  year={1997},
  publisher={IEEE}
}