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BDM+08: Tonio Ball, Evariste Demandt, Isabella Mutschler, Eva Neitzel, Carsten Mehring, Klaus Vogt, Ad Aertsen, and Andreas Schulze-Bonhage. Movement related activity in the high gamma range of the human EEG. NeuroImage, 41(2):302–310, June 2008. URL: http://www.sciencedirect.com/science/article/pii/S1053811908001717 (visited on 2015-07-15), doi:10.1016/j.neuroimage.2008.02.032.
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BSV+18: Joos Behncke, Robin Tibor Schirrmeister, Martin Volker, Jiri Hammer, Petr Marusic, Andreas Schulze-Bonhage, Wolfram Burgard, and Tonio Ball. Cross-paradigm pretraining of convolutional networks improves intracranial eeg decoding. In 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 1046–1053. IEEE, 2018.
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BFK+17: Felix Burget, Lukas Dominique Josef Fiederer, Daniel Kuhner, Martin Völker, Johannes Aldinger, Robin Tibor Schirrmeister, Chau Do, Joschka Boedecker, Bernhard Nebel, Tonio Ball, and others. Acting thoughts: towards a mobile robotic service assistant for users with limited communication skills. In 2017 European Conference on Mobile Robots (ECMR), 1–6. IEEE, 2017.
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CCM+22: Isha R Chavva, Anna L Crawford, Mercy H Mazurek, Matthew M Yuen, Anjali M Prabhat, Sam Payabvash, Gordon Sze, Guido J Falcone, Charles C Matouk, Adam de Havenon, and others. Deep learning applications for acute stroke management. Annals of Neurology, 92(4):574–587, 2022.
CAW+09: Zheng Yang Chin, Kai Keng Ang, Chuanchu Wang, Cuntai Guan, and Haihong Zhang. Multi-class filter bank common spatial pattern for four-class motor imagery BCI. In Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009. EMBC 2009, 571–574. September 2009. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5332383, doi:10.1109/IEMBS.2009.5332383.
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DFE+22: Tri Dao, Daniel Y. Fu, Stefano Ermon, Atri Rudra, and Christopher Ré. Flashattention: fast and memory-efficient exact attention with io-awareness. In NeurIPS. 2022. URL: http://papers.nips.cc/paper\_files/paper/2022/hash/67d57c32e20fd0a7a302cb81d36e40d5-Abstract-Conference.html.
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dS22: missing journal in de2022learning
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HMJ+16: Mehdi Hajinoroozi, Zijing Mao, Tzyy-Ping Jung, Chin-Teng Lin, and Yufei Huang. EEG-based prediction of driver's cognitive performance by deep convolutional neural network. Signal Processing: Image Communication, 47:549–555, September 2016. URL: http://www.sciencedirect.com/science/article/pii/S0923596516300832 (visited on 2016-12-20), doi:10.1016/j.image.2016.05.018.
HPF+16: Jiří Hammer, Tobias Pistohl, Jörg Fischer, Pavel Kršek, Martin Tomášek, Petr Marusič, Andreas Schulze-Bonhage, Ad Aertsen, and Tonio Ball. Predominance of Movement Speed Over Direction in Neuronal Population Signals of Motor Cortex: Intracranial EEG Data and A Simple Explanatory Model. Cerebral Cortex (New York, NY), 26(6):2863–2881, June 2016. URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4869816/ (visited on 2017-01-11), doi:10.1093/cercor/bhw033.
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HMG+14: Stefan Haufe, Frank Meinecke, Kai Görgen, Sven Dähne, John-Dylan Haynes, Benjamin Blankertz, and Felix Bießmann. On the interpretation of weight vectors of linear models in multivariate neuroimaging. NeuroImage, 87:96–110, February 2014. URL: http://www.sciencedirect.com/science/article/pii/S1053811913010914 (visited on 2015-08-07), doi:10.1016/j.neuroimage.2013.10.067.
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HCS+19: Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan, and Pieter Abbeel. Flow++: improving flow-based generative models with variational dequantization and architecture design. In Kamalika Chaudhuri and Ruslan Salakhutdinov, editors, Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA, volume 97 of Proceedings of Machine Learning Research, 2722–2730. PMLR, 2019. URL: http://proceedings.mlr.press/v97/ho19a.html.
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KSA+17: Pieter-Jan Kindermans, Kristof T. Schütt, Maximilian Alber, Klaus-Robert Müller, and Sven Dähne. PatternNet and PatternLRP - Improving the interpretability of neural networks. CoRR, 2017. URL: http://arxiv.org/abs/1705.05598.
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RAA+20: Anirudh Ravula, Chris Alberti, Joshua Ainslie, Li Yang, Philip Minh Pham, Qifan Wang, Santiago Ontanon, Sumit Kumar Sanghai, Vaclav Cvicek, and Zach Fisher. Etc: encoding long and structured inputs in transformers. In 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020). 2020. URL: https://www.aclweb.org/anthology/2020.emnlp-main.19.pdf.
RMS+17: Esteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka Leon Suematsu, Jie Tan, Quoc Le, and Alex Kurakin. Large-Scale Evolution of Image Classifiers. arXiv:1703.01041 [cs], March 2017. arXiv: 1703.01041. URL: http://arxiv.org/abs/1703.01041 (visited on 2017-08-26).
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Sto16: Sebastian Stober. Learning Discriminative Features from Electroencephalography Recordings by Encoding Similarity Constraints. In Bernstein Conference 2016. 2016. doi:10.12751/nncn.bc2016.0223.
SCG14: Sebastian Stober, Daniel J. Cameron, and Jessica A. Grahn. Using Convolutional Neural Networks to Recognize Rhythm Stimuli from Electroencephalography Recordings. In Proceedings of the 27th International Conference on Neural Information Processing Systems, NIPS'14, 1449–1457. Cambridge, MA, USA, 2014. MIT Press. URL: http://dl.acm.org/citation.cfm?id=2968826.2968988 (visited on 2016-12-20).
SLL20: Pascal Sturmfels, Scott Lundberg, and Su-In Lee. Visualizing the impact of feature attribution baselines. Distill, 2020. https://distill.pub/2020/attribution-baselines. doi:10.23915/distill.00022.
SQC+16: Xuyun Sun, Cunle Qian, Zhongqin Chen, Zhaohui Wu, Benyan Luo, and Gang Pan. Remembered or Forgotten?—An EEG-Based Computational Prediction Approach. PLOS ONE, 11(12):e0167497, December 2016. URL: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0167497 (visited on 2017-02-14), doi:10.1371/journal.pone.0167497.
SZS+14: Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus. Intriguing properties of neural networks. In International Conference on Learning Representations. 2014. URL: http://arxiv.org/abs/1312.6199.
TH17: Yousef Rezaei Tabar and Ugur Halici. A novel deep learning approach for classification of EEG motor imagery signals. Journal of Neural Engineering, 14(1):016003, 2017. URL: http://stacks.iop.org/1741-2552/14/i=1/a=016003 (visited on 2017-02-14), doi:10.1088/1741-2560/14/1/016003.
TMA+12: Michael Tangermann, Klaus-Robert Müller, Ad Aertsen, Niels Birbaumer, Christoph Braun, Clemens Brunner, Robert Leeb, Carsten Mehring, Kai J. Miller, Gernot R. Müller-Putz, Guido Nolte, Gert Pfurtscheller, Hubert Preissl, Gerwin Schalk, Alois Schlögl, Carmen Vidaurre, Stephan Waldert, and Benjamin Blankertz. Review of the BCI Competition IV. Frontiers in Neuroscience, July 2012. URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3396284/ (visited on 2015-08-20), doi:10.3389/fnins.2012.00055.
TvdOB16: Lucas Theis, Aäron van den Oord, and Matthias Bethge. A note on the evaluation of generative models. In Yoshua Bengio and Yann LeCun, editors, 4th International Conference on Learning Representations, ICLR 2016, San Juan, Puerto Rico, May 2-4, 2016, Conference Track Proceedings. 2016. URL: http://arxiv.org/abs/1511.01844.
TPL16: Pierre Thodoroff, Joelle Pineau, and Andrew Lim. Learning Robust Features using Deep Learning for Automatic Seizure Detection. In JMLR Workshop and Conference Proceedings, volume 56. 2016. URL: http://www.jmlr.org/proceedings/papers/v56/Thodoroff16.pdf (visited on 2017-02-14).
VSP+17: Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. Attention is all you need. In Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna M. Wallach, Rob Fergus, S. V. N. Vishwanathan, and Roman Garnett, editors, Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, 5998–6008. 2017. URL: https://proceedings.neurips.cc/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html.
VHS+18: Martin Volker, Jiri Hammer, Robin T Schirrmeister, Joos Behncke, Lukas DJ Fiederer, Andreas Schulze-Bonhage, Petr Marusic, Wolfram Burgard, and Tonio Ball. Intracranial error detection via deep learning. In 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 568–575. IEEE, 2018.
VolkerSF+18: Martin Völker, Robin T Schirrmeister, Lukas DJ Fiederer, Wolfram Burgard, and Tonio Ball. Deep transfer learning for error decoding from non-invasive eeg. In 2018 6th International Conference on Brain-Computer Interface (BCI), 1–6. IEEE, 2018.
WZTE18: Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba, and Alexei A. Efros. Dataset distillation. CoRR, 2018. URL: http://arxiv.org/abs/1811.10959, arXiv:1811.10959.
WGS+18: X. Wang, C. A. Gkogkidis, R. T. Schirrmeister, F. A. Heilmeyer, M. Gierthmuehlen, F. Kohler, M. Schuettler, T. Stieglitz, and T. Ball. Deep learning for micro-electrocorticographic (µecog) data. In 2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES), volume, 63–68. 2018. doi:10.1109/IECBES.2018.8626607.
WLSJ13: Zuoguan Wang, Siwei Lyu, Gerwin Schalk, and Qiang Ji. Deep Feature Learning Using Target Priors with Applications in ECoG Signal Decoding for BCI. In Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI '13, 1785–1791. Beijing, China, 2013. AAAI Press. URL: http://dl.acm.org/citation.cfm?id=2540128.2540384 (visited on 2017-01-16).
XRLM22: Sang Michael Xie, Aditi Raghunathan, Percy Liang, and Tengyu Ma. An explanation of in-context learning as implicit bayesian inference. In The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022. OpenReview.net, 2022. URL: https://openreview.net/forum?id=RdJVFCHjUMI.
ZGD+20: missing booktitle in bigbird
ZB21: Bo Zhao and Hakan Bilen. Dataset condensation with differentiable siamese augmentation. In Marina Meila and Tong Zhang, editors, Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event, volume 139 of Proceedings of Machine Learning Research, 12674–12685. PMLR, 2021. URL: http://proceedings.mlr.press/v139/zhao21a.html.
ZMB21: Bo Zhao, Konda Reddy Mopuri, and Hakan Bilen. Dataset condensation with gradient matching. In 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021. OpenReview.net, 2021. URL: https://openreview.net/forum?id=mSAKhLYLSsl.
ZL16: Barret Zoph and Quoc V. Le. Neural Architecture Search with Reinforcement Learning. arXiv:1611.01578 [cs], November 2016. arXiv: 1611.01578. URL: http://arxiv.org/abs/1611.01578 (visited on 2017-08-26).
ZVSL17: Barret Zoph, Vijay Vasudevan, Jonathon Shlens, and Quoc V. Le. Learning Transferable Architectures for Scalable Image Recognition. arXiv:1707.07012 [cs], July 2017. arXiv: 1707.07012. URL: http://arxiv.org/abs/1707.07012 (visited on 2017-08-26).