Laurens van der Maaten

Research Scientist

Computer Vision
Facebook AI Research
Machine Learning

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

Website
Google Scholar Profile
Website
Google Scholar Profile

Latest Publications

PHYRE: A New Benchmark for Physical Reasoning

Anton Bakhtin, Laurens van der Maaten, Justin Johnson, Laura Gustafson, Ross Girshick

NeurIPS - December 10, 2019

Does Object Recognition Work for Everyone?

Terrance DeVries, Ishan Misra, Changhan Wang, Laurens van der Maaten

CVPR - June 16, 2019

Feature Denoising for Improving Adversarial Robustness

Kaiming He, Yuxin Wu, Laurens van der Maaten, Alan Yuille, Cihang Xie

CVPR - June 15, 2019

3D Semantic Segmentation with Submanifold Sparse Convolutional Networks

Benjamin Graham, Laurens van der Maaten, Martin Engelcke

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

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

ArXiv - May 2, 2018

Multi-Scale Dense Networks for Resource Efficient Image Classification

Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, Kilian Weinberger

ICLR 2018 - April 30, 2018

Countering Adversarial Images Using Input Transformations

Chuan Guo, Mayank Rana, Moustapha Cisse, Laurens van der Maaten

ICLR 2018 - April 30, 2018

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

ICCV 2017 - October 22, 2017

Densely Connected Convolutional Networks

Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger

CVPR - 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 2017 - July 21, 2017

Revisiting Visual Question Answering Baselines

Allan Jabri, Armand Joulin, Laurens van der Maaten

ECCV - October 10, 2016

Learning Visual Features from Large Weakly Supervised Data

Armand Joulin, Laurens van der Maaten, Allan Jabri, Nicolas Vasilache

ECCV - October 8, 2016

News

Advancing state-of-the-art image recognition with deep learning on hashtags

May 2, 2018

Facebook Researchers Focus on the Most Challenging Machine Learning Questions at ICML 2016

June 19, 2016