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Pieter-Jan Kindermans
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2020 – today
- 2023
- [c19]Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, Dumitru Erhan:
Phenaki: Variable Length Video Generation from Open Domain Textual Descriptions. ICLR 2023 - [c18]Emanuele Bugliarello, H. Hernan Moraldo, Ruben Villegas, Mohammad Babaeizadeh, Mohammad Taghi Saffar, Han Zhang, Dumitru Erhan, Vittorio Ferrari, Pieter-Jan Kindermans, Paul Voigtlaender:
StoryBench: A Multifaceted Benchmark for Continuous Story Visualization. NeurIPS 2023 - [i17]Emanuele Bugliarello, Hernan Moraldo, Ruben Villegas, Mohammad Babaeizadeh, Mohammad Taghi Saffar, Han Zhang, Dumitru Erhan, Vittorio Ferrari, Pieter-Jan Kindermans, Paul Voigtlaender:
StoryBench: A Multifaceted Benchmark for Continuous Story Visualization. CoRR abs/2308.11606 (2023) - 2022
- [c17]Chengrun Yang, Gabriel Bender, Hanxiao Liu, Pieter-Jan Kindermans, Madeleine Udell, Yifeng Lu, Quoc V. Le, Da Huang:
TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets. NeurIPS 2022 - [i16]Chengrun Yang, Gabriel Bender, Hanxiao Liu, Pieter-Jan Kindermans, Madeleine Udell, Yifeng Lu, Quoc V. Le, Da Huang:
Resource-Constrained Neural Architecture Search on Tabular Datasets. CoRR abs/2204.07615 (2022) - [i15]Pieter-Jan Kindermans, Charles Staats:
When adversarial examples are excusable. CoRR abs/2204.11985 (2022) - [i14]Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, Dumitru Erhan:
Phenaki: Variable Length Video Generation From Open Domain Textual Description. CoRR abs/2210.02399 (2022) - 2021
- [c16]Grace Chu, Okan Arikan, Gabriel Bender, Weijun Wang, Achille Brighton, Pieter-Jan Kindermans, Hanxiao Liu, Berkin Akin, Suyog Gupta, Andrew Howard:
Discovering Multi-Hardware Mobile Models via Architecture Search. CVPR Workshops 2021: 3022-3031 - [c15]Yunyang Xiong, Hanxiao Liu, Suyog Gupta, Berkin Akin, Gabriel Bender, Yongzhe Wang, Pieter-Jan Kindermans, Mingxing Tan, Vikas Singh, Bo Chen:
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators. CVPR 2021: 3825-3834 - 2020
- [c14]Gabriel Bender, Hanxiao Liu, Bo Chen, Grace Chu, Shuyang Cheng, Pieter-Jan Kindermans, Quoc V. Le:
Can Weight Sharing Outperform Random Architecture Search? An Investigation With TuNAS. CVPR 2020: 14311-14320 - [c13]Wei Wen, Hanxiao Liu, Yiran Chen, Hai Helen Li, Gabriel Bender, Pieter-Jan Kindermans:
Neural Predictor for Neural Architecture Search. ECCV (29) 2020: 660-676 - [c12]Jiahui Yu, Pengchong Jin, Hanxiao Liu, Gabriel Bender, Pieter-Jan Kindermans, Mingxing Tan, Thomas S. Huang, Xiaodan Song, Ruoming Pang, Quoc Le:
BigNAS: Scaling up Neural Architecture Search with Big Single-Stage Models. ECCV (7) 2020: 702-717 - [i13]Jiahui Yu, Pengchong Jin, Hanxiao Liu, Gabriel Bender, Pieter-Jan Kindermans, Mingxing Tan, Thomas S. Huang, Xiaodan Song, Ruoming Pang, Quoc V. Le:
BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage Models. CoRR abs/2003.11142 (2020) - [i12]Yunyang Xiong, Hanxiao Liu, Suyog Gupta, Berkin Akin, Gabriel Bender, Pieter-Jan Kindermans, Mingxing Tan, Vikas Singh, Bo Chen:
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators. CoRR abs/2004.14525 (2020) - [i11]Gabriel Bender, Hanxiao Liu, Bo Chen, Grace Chu, Shuyang Cheng, Pieter-Jan Kindermans, Quoc Le:
Can weight sharing outperform random architecture search? An investigation with TuNAS. CoRR abs/2008.06120 (2020) - [i10]Grace Chu, Okan Arikan, Gabriel Bender, Weijun Wang, Achille Brighton, Pieter-Jan Kindermans, Hanxiao Liu, Berkin Akin, Suyog Gupta, Andrew Howard:
Discovering Multi-Hardware Mobile Models via Architecture Search. CoRR abs/2008.08178 (2020)
2010 – 2019
- 2019
- [j6]Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans:
iNNvestigate Neural Networks! J. Mach. Learn. Res. 20: 93:1-93:8 (2019) - [c11]Sara Hooker, Dumitru Erhan, Pieter-Jan Kindermans, Been Kim:
A Benchmark for Interpretability Methods in Deep Neural Networks. NeurIPS 2019: 9734-9745 - [p2]Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo, Maximilian Alber, Kristof T. Schütt, Sven Dähne, Dumitru Erhan, Been Kim:
The (Un)reliability of Saliency Methods. Explainable AI 2019: 267-280 - [p1]David Hübner, Pieter-Jan Kindermans, Thibault Verhoeven, Klaus-Robert Müller, Michael Tangermann:
Rethinking BCI Paradigm and Machine Learning Algorithm as a Symbiosis: Zero Calibration, Guaranteed Convergence and High Decoding Performance. Brain-Computer Interface Research (7) 2019: 63-73 - [i9]Wei Wen, Hanxiao Liu, Hai Li, Yiran Chen, Gabriel Bender, Pieter-Jan Kindermans:
Neural Predictor for Neural Architecture Search. CoRR abs/1912.00848 (2019) - 2018
- [j5]David Hübner, Thibault Verhoeven, Klaus-Robert Müller
, Pieter-Jan Kindermans, Michael Tangermann:
Unsupervised Learning for Brain-Computer Interfaces Based on Event-Related Potentials: Review and Online Comparison [Research Frontier]. IEEE Comput. Intell. Mag. 13(2): 66-67 (2018) - [j4]Iryna Korshunova
Towards Improved Design and Evaluation of Epileptic Seizure Predictors. IEEE Trans. Biomed. Eng. 65(3): 502-510 (2018) - [c10]Pieter-Jan Kindermans, Kristof T. Schütt, Maximilian Alber, Klaus-Robert Müller, Dumitru Erhan, Been Kim, Sven Dähne:
Learning how to explain neural networks: PatternNet and PatternAttribution. ICLR (Poster) 2018 - [c9]Samuel L. Smith, Pieter-Jan Kindermans, Chris Ying, Quoc V. Le:
Don't Decay the Learning Rate, Increase the Batch Size. ICLR (Poster) 2018 - [c8]Gabriel Bender, Pieter-Jan Kindermans, Barret Zoph, Vijay Vasudevan, Quoc V. Le:
Understanding and Simplifying One-Shot Architecture Search. ICML 2018: 549-558 - [i8]Sara Hooker, Dumitru Erhan, Pieter-Jan Kindermans, Been Kim:
Evaluating Feature Importance Estimates. CoRR abs/1806.10758 (2018) - [i7]Maximilian Alber, Irwan Bello, Barret Zoph, Pieter-Jan Kindermans, Prajit Ramachandran, Quoc V. Le:
Backprop Evolution. CoRR abs/1808.02822 (2018) - [i6]Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans:
iNNvestigate neural networks! CoRR abs/1808.04260 (2018) - 2017
- [c7]David Hübner, Pieter-Jan Kindermans, Thibault Verhoeven, Michael Tangermann:
Improving Learning from Label proportions by Reducing the Feature Dimensionality. GBCIC 2017 - [c6]David Hübner, Thibault Verhoeven, Pieter-Jan Kindermans, Michael Tangermann:
Mixing two Unsupervised estimators for Event-Related potential decoding: an Online Evaluation. GBCIC 2017 - [c5]Kristof Schütt, Pieter-Jan Kindermans, Huziel Enoc Sauceda Felix, Stefan Chmiela, Alexandre Tkatchenko, Klaus-Robert Müller:
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions. NIPS 2017: 991-1001 - [c4]Maximilian Alber, Pieter-Jan Kindermans, Kristof Schütt, Klaus-Robert Müller, Fei Sha:
An Empirical Study on The Properties of Random Bases for Kernel Methods. NIPS 2017: 2763-2774 - [i5]David Hübner, Thibault Verhoeven, Konstantin Schmid, Klaus-Robert Müller, Michael Tangermann, Pieter-Jan Kindermans:
Learning from Label Proportions in Brain-Computer Interfaces: Online Unsupervised Learning with Guarantees. CoRR abs/1701.07213 (2017) - [i4]Pieter-Jan Kindermans, Kristof T. Schütt, Maximilian Alber, Klaus-Robert Müller, Sven Dähne:
PatternNet and PatternLRP - Improving the interpretability of neural networks. CoRR abs/1705.05598 (2017) - [i3]Samuel L. Smith, Pieter-Jan Kindermans, Quoc V. Le:
Don't Decay the Learning Rate, Increase the Batch Size. CoRR abs/1711.00489 (2017) - [i2]Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo, Maximilian Alber, Kristof T. Schütt, Sven Dähne, Dumitru Erhan, Been Kim:
The (Un)reliability of saliency methods. CoRR abs/1711.00867 (2017) - 2016
- [j3]Di Wu, Lionel Pigou, Pieter-Jan Kindermans, Nam Do-Hoang Le, Ling Shao
Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 38(8): 1583-1597 (2016) - [i1]Pieter-Jan Kindermans, Kristof Schütt, Klaus-Robert Müller, Sven Dähne:
Investigating the influence of noise and distractors on the interpretation of neural networks. CoRR abs/1611.07270 (2016) - 2015
- [j2]Jonas Degrave, Michael Burm, Pieter-Jan Kindermans, Joni Dambre
Transfer learning of gaits on a quadrupedal robot. Adapt. Behav. 23(2): 69-82 (2015) - 2014
- [b1]Pieter-Jan Kindermans:
A Bayesian machine learning framework for true zero-training brain-computer interfaces. Ghent University, Belgium, 2014 - [c3]Lionel Pigou, Sander Dieleman, Pieter-Jan Kindermans, Benjamin Schrauwen:
Sign Language Recognition Using Convolutional Neural Networks. ECCV Workshops (1) 2014: 572-578 - 2013
- [j1]Pieter-Jan Kindermans, Hannes Verschore, Benjamin Schrauwen:
A Unified Probabilistic Approach to Improve Spelling in an Event-Related Potential-Based Brain-Computer Interface. IEEE Trans. Biomed. Eng. 60(10): 2696-2705 (2013) - 2012
- [c2]Hannes Verschore, Pieter-Jan Kindermans, David Verstraeten, Benjamin Schrauwen:
Dynamic Stopping Improves the Speed and Accuracy of a P300 Speller. ICANN (1) 2012: 661-668 - [c1]Pieter-Jan Kindermans, Hannes Verschore, David Verstraeten, Benjamin Schrauwen:
A P300 BCI for the Masses: Prior Information Enables Instant Unsupervised Spelling. NIPS 2012: 719-727
Coauthor Index
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