Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox

Picture for Pieter-Jan Kindermans

Discovering Multi-Hardware Mobile Models via Architecture Search


Aug 18, 2020
Grace Chu, Okan Arikan, Gabriel Bender, Weijun Wang, Achille Brighton, Pieter-Jan Kindermans, Hanxiao Liu, Berkin Akin, Suyog Gupta, Andrew Howard


  Access Paper or Ask Questions

Can weight sharing outperform random architecture search? An investigation with TuNAS


Aug 13, 2020
Gabriel Bender, Hanxiao Liu, Bo Chen, Grace Chu, Shuyang Cheng, Pieter-Jan Kindermans, Quoc Le

* Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 14323-14332 
* Published at CVPR 2020 

  Access Paper or Ask Questions

MobileDets: Searching for Object Detection Architectures for Mobile Accelerators


Apr 30, 2020
Yunyang Xiong, Hanxiao Liu, Suyog Gupta, Berkin Akin, Gabriel Bender, Pieter-Jan Kindermans, Mingxing Tan, Vikas Singh, Bo Chen


  Access Paper or Ask Questions

BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage Models


Mar 24, 2020
Jiahui Yu, Pengchong Jin, Hanxiao Liu, Gabriel Bender, Pieter-Jan Kindermans, Mingxing Tan, Thomas Huang, Xiaodan Song, Ruoming Pang, Quoc Le

* Technical report 

  Access Paper or Ask Questions

Neural Predictor for Neural Architecture Search


Dec 02, 2019
Wei Wen, Hanxiao Liu, Hai Li, Yiran Chen, Gabriel Bender, Pieter-Jan Kindermans


  Access Paper or Ask Questions

iNNvestigate neural networks!


Aug 13, 2018
Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans


  Access Paper or Ask Questions

Backprop Evolution


Aug 08, 2018
Maximilian Alber, Irwan Bello, Barret Zoph, Pieter-Jan Kindermans, Prajit Ramachandran, Quoc Le


  Access Paper or Ask Questions

Evaluating Feature Importance Estimates


Jun 28, 2018
Sara Hooker, Dumitru Erhan, Pieter-Jan Kindermans, Been Kim

* presented at 2018 ICML Workshop on Human Interpretability in Machine Learning (WHI 2018), Stockholm, Sweden 

  Access Paper or Ask Questions

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


Feb 24, 2018
Samuel L. Smith, Pieter-Jan Kindermans, Chris Ying, Quoc V. Le

* 11 pages, 8 figures. Published as a conference paper at ICLR 2018 

  Access Paper or Ask Questions

SchNet: A continuous-filter convolutional neural network for modeling quantum interactions


Dec 19, 2017
Kristof T. Schütt, Pieter-Jan Kindermans, Huziel E. Sauceda, Stefan Chmiela, Alexandre Tkatchenko, Klaus-Robert Müller

* Advances in Neural Information Processing Systems 30 (2017), pp. 992-1002 

  Access Paper or Ask Questions

The (Un)reliability of saliency methods


Nov 02, 2017
Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo, Maximilian Alber, Kristof T. Schütt, Sven Dähne, Dumitru Erhan, Been Kim


  Access Paper or Ask Questions

Learning how to explain neural networks: PatternNet and PatternAttribution


Oct 24, 2017
Pieter-Jan Kindermans, Kristof T. Schütt, Maximilian Alber, Klaus-Robert Müller, Dumitru Erhan, Been Kim, Sven Dähne


  Access Paper or Ask Questions

Investigating the influence of noise and distractors on the interpretation of neural networks


Nov 22, 2016
Pieter-Jan Kindermans, Kristof Schütt, Klaus-Robert Müller, Sven Dähne

* Presented at NIPS 2016 Workshop on Interpretable Machine Learning in Complex Systems 

  Access Paper or Ask Questions