Pieter-Jan Kindermans

According to our database, Pieter-Jan Kindermans authored at least 39 papers between 2012 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

StoryBench: A Multifaceted Benchmark for Continuous Story Visualization.

Emanuele Bugliarello, H. Hernan Moraldo, Ruben Villegas, Mohammad Babaeizadeh, Mohammad Taghi Saffar, Han Zhang, Dumitru Erhan, Vittorio Ferrari, Pieter-Jan Kindermans, Paul Voigtlaender

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Phenaki: Variable Length Video Generation from Open Domain Textual Descriptions.

Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, Dumitru Erhan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Phenaki: Variable Length Video Generation From Open Domain Textual Description.

Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, Dumitru Erhan

CoRR, 2022

When adversarial examples are excusable.

Pieter-Jan Kindermans, Charles Staats

CoRR, 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

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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

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

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

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

CoRR, 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

Proceedings of the Computer Vision - ECCV 2020, 2020

Neural Predictor for Neural Architecture Search.

Wei Wen, Hanxiao Liu, Yiran Chen, Hai Helen Li, Gabriel Bender, Pieter-Jan Kindermans

Proceedings of the Computer Vision - ECCV 2020, 2020

Can Weight Sharing Outperform Random Architecture Search? An Investigation With TuNAS.

Gabriel Bender, Hanxiao Liu, Bo Chen, Grace Chu, Shuyang Cheng, Pieter-Jan Kindermans, Quoc V. Le

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

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

Proceedings of the Brain-Computer Interface Research - A State-of-the-Art Summary 7, 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

Proceedings of the Explainable AI: Interpreting, 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

A Benchmark for Interpretability Methods in Deep Neural Networks.

Sara Hooker, Dumitru Erhan, Pieter-Jan Kindermans, Been Kim

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

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

Backprop Evolution.

Maximilian Alber, Irwan Bello, Barret Zoph, Pieter-Jan Kindermans, Prajit Ramachandran, Quoc V. Le

CoRR, 2018

Evaluating Feature Importance Estimates.

Sara Hooker, Dumitru Erhan, Pieter-Jan Kindermans, Been Kim

CoRR, 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

Understanding and Simplifying One-Shot Architecture Search.

Gabriel Bender, Pieter-Jan Kindermans, Barret Zoph, Vijay Vasudevan, Quoc V. Le

Proceedings of the 35th International Conference on Machine Learning, 2018

Don't Decay the Learning Rate, Increase the Batch Size.

Samuel L. Smith, Pieter-Jan Kindermans, Chris Ying, Quoc V. Le

Proceedings of the 6th International Conference on Learning Representations, 2018

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

Proceedings of the 6th International Conference on Learning Representations, 2018

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

Don't Decay the Learning Rate, Increase the Batch Size.

Samuel L. Smith, Pieter-Jan Kindermans, Quoc V. Le

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

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

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

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 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

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Mixing two Unsupervised estimators for Event-Related potential decoding: an Online Evaluation.

David Hübner, Thibault Verhoeven, Pieter-Jan Kindermans, Michael Tangermann

Proceedings of the From Vision to Reality, 2017

Improving Learning from Label proportions by Reducing the Feature Dimensionality.

David Hübner, Pieter-Jan Kindermans, Thibault Verhoeven, Michael Tangermann

Proceedings of the From Vision to Reality, 2017

2016

Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition.

Di Wu, Lionel Pigou, Pieter-Jan Kindermans, Nam Do-Hoang Le, Ling Shao, Joni Dambre, Jean-Marc Odobez

IEEE Trans. Pattern Anal. Mach. Intell., 2016

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

2015

Transfer learning of gaits on a quadrupedal robot.

Jonas Degrave, Michael Burm, Pieter-Jan Kindermans, Joni Dambre, Francis Wyffels

Adapt. Behav., 2015

2014

A Bayesian machine learning framework for true zero-training brain-computer interfaces.

Pieter-Jan Kindermans

PhD thesis, 2014

Sign Language Recognition Using Convolutional Neural Networks.

Lionel Pigou, Sander Dieleman, Pieter-Jan Kindermans, Benjamin Schrauwen

Proceedings of the Computer Vision - ECCV 2014 Workshops, 2014

2013

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

2012

A P300 BCI for the Masses: Prior Information Enables Instant Unsupervised Spelling.

Pieter-Jan Kindermans, Hannes Verschore, David Verstraeten, Benjamin Schrauwen

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Dynamic Stopping Improves the Speed and Accuracy of a P300 Speller.

Hannes Verschore, Pieter-Jan Kindermans, David Verstraeten, Benjamin Schrauwen

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012