I am a research scientist at Facebook AI Research since March 2015, with a focus on machine learning and computer vision. Prior, I worked as an assistant professor at Delft University of Technology and as a post-doctoral researcher at University of California, San Diego. I received my PhD from Tilburg University in 2009.
Interests
Machine learning and computer vision
Latest Publications
ICML - July 19, 2021
Making Paper Reviewing Robust to Bid Manipulation Attacks
Ruihan Wu, Chuan Guo, Felix Wu, Rahul Kidambi, Laurens van der Maaten, Kilian Q. Weinberger
Information and Inference: a Journal of the IMA - January 18, 2021
Secure multiparty computations in floating-point arithmetic
Chuan Guo, Awni Hannun, Brian Knott, Laurens van der Maaten, Mark Tygert, Ruiyu Zhu
ICML - December 1, 2020
Certified Data Removal from Machine Learning Models
Chuan Guo, Tom Goldstein, Awni Hannun, Laurens van der Maaten
CVPR - June 19, 2020
Self-Supervised Learning of Pretext-Invariant Representations
Ishan Misra, Laurens van der Maaten
NeurIPS - December 10, 2019
PHYRE: A New Benchmark for Physical Reasoning
Anton Bakhtin, Laurens van der Maaten, Justin Johnson, Laura Gustafson, Ross Girshick
CVPR - June 16, 2019
Does Object Recognition Work for Everyone?
Terrance DeVries, Ishan Misra, Changhan Wang, Laurens van der Maaten
CVPR - June 15, 2019
Feature Denoising for Improving Adversarial Robustness
Kaiming He, Yuxin Wu, Laurens van der Maaten, Alan Yuille, Cihang Xie
CVPR 2018 - June 18, 2018
Separating Self-Expression and Visual Content in Hashtag Supervision
Andreas Veit, Maximilian Nickel, Serge Belongie, Laurens van der Maaten
CVPR 2018 - June 18, 2018
Learning by Asking Questions
Ishan Misra, Ross Girshick, Rob Fergus, Martial Hebert, Abhinav Gupta, Laurens van der Maaten
CVPR 2018 - June 18, 2018
CondenseNet: An Efficient DenseNet using Learned Group Convolutions
Gao Huang, Shichen Liu, Laurens van der Maaten, Kilian Q. Weinberger
CVPR 2018 - June 18, 2018
3D Semantic Segmentation with Submanifold Sparse Convolutional Networks
Benjamin Graham, Laurens van der Maaten, Martin Engelcke
ArXiv - May 2, 2018
Exploring the Limits of Weakly Supervised Pretraining
Dhruv Mahajan, Ross Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, Ashwin Bharambe, Laurens van der Maaten
ICLR 2018 - April 30, 2018
Multi-Scale Dense Networks for Resource Efficient Image Classification
Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, Kilian Q. Weinberger
ICLR 2018 - April 30, 2018
Countering Adversarial Images Using Input Transformations
Chuan Guo, Mayank Rana, Moustapha Cisse, Laurens van der Maaten
ICCV 2017 - October 22, 2017
Inferring and Executing Programs for Visual Reasoning
Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Judy Hoffman, Li Fei-Fei, Larry Zitnick, Ross Girshick
ICCV 2017 - October 22, 2017
Learning Visual N-Grams from Web Data
Ang Li, Allan Jabri, Armand Joulin, Laurens van der Maaten
CVPR 2017 - July 21, 2017
CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning
Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Li Fei-Fei, Larry Zitnick, Ross Girshick
CVPR - July 21, 2017
Densely Connected Convolutional Networks
Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger
ECCV - October 10, 2016
Revisiting Visual Question Answering Baselines
Allan Jabri, Armand Joulin, Laurens van der Maaten
ECCV - October 8, 2016
Learning Visual Features from Large Weakly Supervised Data
Armand Joulin, Laurens van der Maaten, Allan Jabri, Nicolas Vasilache
