Dynamic Stopping Improves the Speed and Accuracy of a P300 Speller. - Hannes Verschore; Pieter-Jan Kindermans; David Verstraeten; Benjamin Schrauwen (ICANN (1), 2012)

A P300 BCI for the Masses: Prior Information Enables Instant Unsupervised Spelling. - Pieter-Jan Kindermans; Hannes Verschore; David Verstraeten; Benjamin Schrauwen (NIPS, 2012)

A Unified Probabilistic Approach to Improve Spelling in an Event-Related Potential-Based Brain-Computer Interface. - Pieter-Jan Kindermans; Hannes Verschore; Benjamin Schrauwen (IEEE Trans. Biomed. Eng., 2013)

Sign Language Recognition Using Convolutional Neural Networks. - Lionel Pigou; Sander Dieleman; Pieter-Jan Kindermans; Benjamin Schrauwen (ECCV Workshops (1), 2014)

A Bayesian machine learning framework for true zero-training brain-computer interfaces. - Pieter-Jan Kindermans (2014)

Transfer learning of gaits on a quadrupedal robot. - Jonas Degrave; Michael Burm; Pieter-Jan Kindermans; Joni Dambre; Francis Wyffels (Adapt. Behav., 2015)

Investigating the influence of noise and distractors on the interpretation of neural networks. - Pieter-Jan Kindermans; Kristof Schütt; Klaus-Robert Müller; Sven Dähne (CoRR, 2016)

Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition. - Di Wu 009; Lionel Pigou; Pieter-Jan Kindermans; Nam Do-Hoang Le; Ling Shao 001; Joni Dambre; Jean-Marc Odobez (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

Improving Learning from Label proportions by Reducing the Feature Dimensionality. - David Hübner; Pieter-Jan Kindermans; Thibault Verhoeven; Michael Tangermann (GBCIC, 2017)

Mixing two Unsupervised estimators for Event-Related potential decoding: an Online Evaluation. - David Hübner; Thibault Verhoeven; Pieter-Jan Kindermans; Michael Tangermann (GBCIC, 2017)

An Empirical Study on The Properties of Random Bases for Kernel Methods. - Maximilian Alber; Pieter-Jan Kindermans; Kristof Schütt; Klaus-Robert Müller; Fei Sha (NIPS, 2017)

SchNet: A continuous-filter convolutional neural network for modeling quantum interactions. - Kristof Schütt; Pieter-Jan Kindermans; Huziel Enoc Sauceda Felix; Stefan Chmiela; Alexandre Tkatchenko; Klaus-Robert Müller (NIPS, 2017)

Learning from Label Proportions in Brain-Computer Interfaces: Online Unsupervised Learning with Guarantees. - David Hübner; Thibault Verhoeven; Konstantin Schmid; Klaus-Robert Müller; Michael Tangermann; Pieter-Jan Kindermans (CoRR, 2017)

PatternNet and PatternLRP - Improving the interpretability of neural networks. - Pieter-Jan Kindermans; Kristof T. Schütt; Maximilian Alber; Klaus-Robert Müller; Sven Dähne (CoRR, 2017)

Don't Decay the Learning Rate, Increase the Batch Size. - Samuel L. Smith; Pieter-Jan Kindermans; Quoc V. Le (CoRR, 2017)

The (Un)reliability of saliency methods. - Pieter-Jan Kindermans; Sara Hooker; Julius Adebayo; Maximilian Alber; Kristof T. Schütt; Sven Dähne; Dumitru Erhan; Been Kim (CoRR, 2017)

Learning how to explain neural networks: PatternNet and PatternAttribution. - Pieter-Jan Kindermans; Kristof T. Schütt; Maximilian Alber; Klaus-Robert Müller; Dumitru Erhan; Been Kim; Sven Dähne (ICLR (Poster), 2018)

Don't Decay the Learning Rate, Increase the Batch Size. - Samuel L. Smith; Pieter-Jan Kindermans; Chris Ying; Quoc V. Le (ICLR (Poster), 2018)

Understanding and Simplifying One-Shot Architecture Search. - Gabriel Bender; Pieter-Jan Kindermans; Barret Zoph; Vijay Vasudevan; Quoc V. Le (ICML, 2018)

Unsupervised Learning for Brain-Computer Interfaces Based on Event-Related Potentials: Review and Online Comparison [Research Frontier]. - David Hübner; Thibault Verhoeven; Klaus-Robert Müller; Pieter-Jan Kindermans; Michael Tangermann (IEEE Comput. Intell. Mag., 2018)

Evaluating Feature Importance Estimates. - Sara Hooker; Dumitru Erhan; Pieter-Jan Kindermans; Been Kim (CoRR, 2018)

Backprop Evolution. - Maximilian Alber; Irwan Bello; Barret Zoph; Pieter-Jan Kindermans; Prajit Ramachandran; Quoc V. Le (CoRR, 2018)

Towards Improved Design and Evaluation of Epileptic Seizure Predictors. - Iryna Korshunova; Pieter-Jan Kindermans; Jonas Degrave; Thibault Verhoeven; Benjamin H. Brinkmann; Joni Dambre (IEEE Trans. Biomed. Eng., 2018)

A Benchmark for Interpretability Methods in Deep Neural Networks. - Sara Hooker; Dumitru Erhan; Pieter-Jan Kindermans; Been Kim (NeurIPS, 2019)

iNNvestigate Neural Networks! - Maximilian Alber; Sebastian Lapuschkin; Philipp Seegerer; Miriam Hägele; Kristof T. Schütt; Grégoire Montavon; Wojciech Samek; Klaus-Robert Müller; Sven Dähne; Pieter-Jan Kindermans (J. Mach. Learn. Res., 2019)

The (Un)reliability of Saliency Methods. - Pieter-Jan Kindermans; Sara Hooker; Julius Adebayo; Maximilian Alber; Kristof T. Schütt; Sven Dähne; Dumitru Erhan; Been Kim (Explainable AI, 2019)

Rethinking BCI Paradigm and Machine Learning Algorithm as a Symbiosis: Zero Calibration, Guaranteed Convergence and High Decoding Performance. - David Hübner; Pieter-Jan Kindermans; Thibault Verhoeven; Klaus-Robert Müller; Michael Tangermann (Brain-Computer Interface Research (7), 2019)

Can Weight Sharing Outperform Random Architecture Search? An Investigation With TuNAS. - Gabriel Bender; Hanxiao Liu; Bo Chen 019; Grace Chu; Shuyang Cheng; Pieter-Jan Kindermans; Quoc V. Le (CVPR, 2020)

Neural Predictor for Neural Architecture Search. - Wei Wen; Hanxiao Liu; Yiran Chen 001; Hai Helen Li; Gabriel Bender; Pieter-Jan Kindermans (ECCV (29), 2020)

BigNAS: Scaling up Neural Architecture Search with Big Single-Stage Models. - Jiahui Yu; Pengchong Jin; Hanxiao Liu; Gabriel Bender; Pieter-Jan Kindermans; Mingxing Tan; Thomas S. Huang; Xiaodan Song; Ruoming Pang; Quoc Le 001 (ECCV (7), 2020)

MobileDets: Searching for Object Detection Architectures for Mobile Accelerators. - Yunyang Xiong; Hanxiao Liu; Suyog Gupta; Berkin Akin; Gabriel Bender; Pieter-Jan Kindermans; Mingxing Tan; Vikas Singh; Bo Chen 019 (CoRR, 2020)

Discovering Multi-Hardware Mobile Models via Architecture Search. - Grace Chu; Okan Arikan; Gabriel Bender; Weijun Wang; Achille Brighton; Pieter-Jan Kindermans; Hanxiao Liu; Berkin Akin; Suyog Gupta; Andrew Howard 002 (CVPR Workshops, 2021)

MobileDets: Searching for Object Detection Architectures for Mobile Accelerators. - Yunyang Xiong; Hanxiao Liu; Suyog Gupta; Berkin Akin; Gabriel Bender; Yongzhe Wang; Pieter-Jan Kindermans; Mingxing Tan; Vikas Singh; Bo Chen 019 (CVPR, 2021)

TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets. - Chengrun Yang; Gabriel Bender; Hanxiao Liu; Pieter-Jan Kindermans; Madeleine Udell; Yifeng Lu; Quoc V. Le; Da Huang (NeurIPS, 2022)

Resource-Constrained Neural Architecture Search on Tabular Datasets. - Chengrun Yang; Gabriel Bender; Hanxiao Liu; Pieter-Jan Kindermans; Madeleine Udell; Yifeng Lu; Quoc V. Le; Da Huang (CoRR, 2022)

When adversarial examples are excusable. - Pieter-Jan Kindermans; Charles Staats (CoRR, 2022)

Phenaki: Variable Length Video Generation From Open Domain Textual Description. - Ruben Villegas; Mohammad Babaeizadeh; Pieter-Jan Kindermans; Hernan Moraldo; Han Zhang 010; Mohammad Taghi Saffar; Santiago Castro; Julius Kunze; Dumitru Erhan (CoRR, 2022)

Phenaki: Variable Length Video Generation from Open Domain Textual Descriptions. - Ruben Villegas; Mohammad Babaeizadeh; Pieter-Jan Kindermans; Hernan Moraldo; Han Zhang 010; Mohammad Taghi Saffar; Santiago Castro; Julius Kunze; Dumitru Erhan (ICLR, 2023)

StoryBench: A Multifaceted Benchmark for Continuous Story Visualization. - Emanuele Bugliarello; H. Hernan Moraldo; Ruben Villegas; Mohammad Babaeizadeh; Mohammad Taghi Saffar; Han Zhang 010; Dumitru Erhan; Vittorio Ferrari; Pieter-Jan Kindermans; Paul Voigtlaender (NeurIPS, 2023)

What Are You Doing? A Closer Look at Controllable Human Video Generation. - Emanuele Bugliarello; Anurag Arnab; Roni Paiss; Pieter-Jan Kindermans; Cordelia Schmid (CoRR, 2025)