Laurens van der Maaten

124 papers A* 29A 6B 8Journal 64Unranked 16

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Law of the Weakest Link: Cross Capabilities of Large Language Models. ICLR Ming Zhong, Aston Zhang, Xuewei Wang, Rui Hou, Wenhan Xiong, Chenguang Zhu, Zhengxing Chen, Liang Tan, Chloe Bi, Mike Lewis, Sravya Popuri, Sharan Narang, Melanie Kambadur, Dhruv Mahajan, Sergey Edunov, Jiawei Han, Laurens van der Maaten
2025	J	`jnl`	NOMAD Projection. CoRR Brandon Duderstadt, Zach Nussbaum, Laurens van der Maaten
2025	J	`jnl`	RoFL: Robust Fingerprinting of Language Models. CoRR Yun-Yun Tsai, Chuan Guo, Junfeng Yang, Laurens van der Maaten
2024	J	`jnl`	Guarantees of confidentiality via Hammersley-Chapman-Robbins bounds. CoRR Kamalika Chaudhuri, Chuan Guo, Laurens van der Maaten, Saeed Mahloujifar, Mark Tygert
2024	J	`jnl`	Guarantees of confidentiality via Hammersley-Chapman-Robbins bounds. Trans. Mach. Learn. Res. Kamalika Chaudhuri, Chuan Guo, Laurens van der Maaten, Saeed Mahloujifar, Mark Tygert
2024	J	`jnl`	Law of the Weakest Link: Cross Capabilities of Large Language Models. CoRR Ming Zhong, Aston Zhang, Xuewei Wang, Rui Hou, Wenhan Xiong, Chenguang Zhu, Zhengxing Chen, Liang Tan, Chloe Bi, Mike Lewis, Sravya Popuri, Sharan Narang, Melanie Kambadur, Dhruv Mahajan, Sergey Edunov, Jiawei Han, Laurens van der Maaten
2023	J	`jnl`	Beyond web-scraping: Crowd-sourcing a geographically diverse image dataset. CoRR Vikram V. Ramaswamy, Sing Yu Lin, Dora Zhao, Aaron B. Adcock, Laurens van der Maaten, Deepti Ghadiyaram, Olga Russakovsky
2023	A*	`conf`	GeoDE: a Geographically Diverse Evaluation Dataset for Object Recognition. NeurIPS Vikram V. Ramaswamy, Sing Yu Lin, Dora Zhao, Aaron Adcock, Laurens van der Maaten, Deepti Ghadiyaram, Olga Russakovsky
2022	J	`jnl`	A Systematic Study of Bias Amplification. CoRR Melissa Hall, Laurens van der Maaten, Laura Gustafson, Aaron Adcock
2022	A*	`conf`	Bounding Training Data Reconstruction in Private (Deep) Learning. ICML Chuan Guo, Brian Karrer, Kamalika Chaudhuri, Laurens van der Maaten
2022	J	`jnl`	Bounding Training Data Reconstruction in Private (Deep) Learning. CoRR Chuan Guo, Brian Karrer, Kamalika Chaudhuri, Laurens van der Maaten
2022	J	`jnl`	Convolutional Networks with Dense Connectivity. IEEE Trans. Pattern Anal. Mach. Intell. Gao Huang, Zhuang Liu, Geoff Pleiss, Laurens van der Maaten, Kilian Q. Weinberger
2022	A	`conf`	Data Appraisal Without Data Sharing. AISTATS Xinlei Xu, Awni Y. Hannun, Laurens van der Maaten
2022	A*	`conf`	EIFFeL: Ensuring Integrity for Federated Learning. CCS Amrita Roy Chowdhury, Chuan Guo, Somesh Jha, Laurens van der Maaten
2022	A*	`conf`	Measuring Data Leakage in Machine-Learning Models with Fisher Information (Extended Abstract). IJCAI Awni Y. Hannun, Chuan Guo, Laurens van der Maaten
2022	A*	`conf`	Omnivore: A Single Model for Many Visual Modalities. CVPR Rohit Girdhar, Mannat Singh, Nikhila Ravi, Laurens van der Maaten, Armand Joulin, Ishan Misra
2022	J	`jnl`	Omnivore: A Single Model for Many Visual Modalities. CoRR Rohit Girdhar, Mannat Singh, Nikhila Ravi, Laurens van der Maaten, Armand Joulin, Ishan Misra
2022	A*	`conf`	Revisiting Weakly Supervised Pre-Training of Visual Perception Models. CVPR Mannat Singh, Laura Gustafson, Aaron Adcock, Vinicius de Freitas Reis, Bugra Gedik, Raj Prateek Kosaraju, Dhruv Mahajan, Ross B. Girshick, Piotr Dollár, Laurens van der Maaten
2022	J	`jnl`	Revisiting Weakly Supervised Pre-Training of Visual Perception Models. CoRR Mannat Singh, Laura Gustafson, Aaron Adcock, Vinicius de Freitas Reis, Bugra Gedik, Raj Prateek Kosaraju, Dhruv Mahajan, Ross B. Girshick, Piotr Dollár, Laurens van der Maaten
2022	A	`conf`	Scaling up Instance Segmentation using Approximately Localized Phrases. BMVC Karan Desai, Ishan Misra, Justin Johnson, Laurens van der Maaten
2022	J	`jnl`	Submix: Practical Private Prediction for Large-Scale Language Models. CoRR Antonio Ginart, Laurens van der Maaten, James Zou, Chuan Guo
2021	A*	`conf`	CrypTen: Secure Multi-Party Computation Meets Machine Learning. NeurIPS Brian Knott, Shobha Venkataraman, Awni Y. Hannun, Shubho Sengupta, Mark Ibrahim, Laurens van der Maaten
2021	J	`jnl`	CrypTen: Secure Multi-Party Computation Meets Machine Learning. CoRR Brian Knott, Shobha Venkataraman, Awni Y. Hannun, Shubho Sengupta, Mark Ibrahim, Laurens van der Maaten
2021	J	`jnl`	EIFFeL: Ensuring Integrity for Federated Learning. CoRR Amrita Roy Chowdhury, Chuan Guo, Somesh Jha, Laurens van der Maaten
2021	A*	`conf`	Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems. NeurIPS Ruihan Wu, Chuan Guo, Awni Y. Hannun, Laurens van der Maaten
2021	J	`jnl`	Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems. CoRR Ruihan Wu, Chuan Guo, Awni Y. Hannun, Laurens van der Maaten
2021	A*	`conf`	Making Paper Reviewing Robust to Bid Manipulation Attacks. ICML Ruihan Wu, Chuan Guo, Felix Wu, Rahul Kidambi, Laurens van der Maaten, Kilian Q. Weinberger
2021	J	`jnl`	Making Paper Reviewing Robust to Bid Manipulation Attacks. CoRR Ruihan Wu, Chuan Guo, Felix Wu, Rahul Kidambi, Laurens van der Maaten, Kilian Q. Weinberger
2021	J	`jnl`	Measuring Data Leakage in Machine-Learning Models with Fisher Information. CoRR Awni Y. Hannun, Chuan Guo, Laurens van der Maaten
2021	A	`conf`	Measuring data leakage in machine-learning models with Fisher information. UAI Awni Y. Hannun, Chuan Guo, Laurens van der Maaten
2021	J	`jnl`	Physical Reasoning Using Dynamics-Aware Models. CoRR Eltayeb Ahmed, Anton Bakhtin, Laurens van der Maaten, Rohit Girdhar
2020	A*	`conf`	Certified Data Removal from Machine Learning Models. ICML Chuan Guo, Tom Goldstein, Awni Y. Hannun, Laurens van der Maaten
2020	J	`jnl`	Convolutional Networks with Dense Connectivity. CoRR Gao Huang, Zhuang Liu, Geoff Pleiss, Laurens van der Maaten, Kilian Q. Weinberger
2020	J	`jnl`	Data Appraisal Without Data Sharing. CoRR Mimee Xu, Laurens van der Maaten, Awni Y. Hannun
2020	J	`jnl`	Forward Prediction for Physical Reasoning. CoRR Rohit Girdhar, Laura Gustafson, Aaron Adcock, Laurens van der Maaten
2020	J	`jnl`	Secure multiparty computations in floating-point arithmetic. CoRR Chuan Guo, Awni Y. Hannun, Brian Knott, Laurens van der Maaten, Mark Tygert, Ruiyu Zhu
2020	A*	`conf`	Self-Supervised Learning of Pretext-Invariant Representations. CVPR Ishan Misra, Laurens van der Maaten
2020	J	`jnl`	The Trade-Offs of Private Prediction. CoRR Laurens van der Maaten, Awni Y. Hannun
2019	A*	`conf`	Anytime Stereo Image Depth Estimation on Mobile Devices. ICRA Yan Wang, Zihang Lai, Gao Huang, Brian H. Wang, Laurens van der Maaten, Mark E. Campbell, Kilian Q. Weinberger
2019	J	`jnl`	Binary Image Selection (BISON): Interpretable Evaluation of Visual Grounding. CoRR Hexiang Hu, Ishan Misra, Laurens van der Maaten
2019	J	`jnl`	Certified Data Removal from Machine Learning Models. CoRR Chuan Guo, Tom Goldstein, Awni Y. Hannun, Laurens van der Maaten
2019	A*	`conf`	Defense Against Adversarial Images Using Web-Scale Nearest-Neighbor Search. CVPR Abhimanyu Dubey, Laurens van der Maaten, Zeki Yalniz, Yixuan Li, Dhruv Mahajan
2019	J	`jnl`	Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search. CoRR Abhimanyu Dubey, Laurens van der Maaten, Zeki Yalniz, Yixuan Li, Dhruv Mahajan
2019	—	`conf`	Does Object Recognition Work for Everyone? CVPR Workshops Terrance DeVries, Ishan Misra, Changhan Wang, Laurens van der Maaten
2019	J	`jnl`	Does Object Recognition Work for Everyone? CoRR Terrance DeVries, Ishan Misra, Changhan Wang, Laurens van der Maaten
2019	—	`conf`	Evaluating Text-to-Image Matching using Binary Image Selection (BISON). ICCV Workshops Hexiang Hu, Ishan Misra, Laurens van der Maaten
2019	A*	`conf`	Feature Denoising for Improving Adversarial Robustness. CVPR Cihang Xie, Yuxin Wu, Laurens van der Maaten, Alan L. Yuille, Kaiming He
2019	J	`jnl`	Measuring Dataset Granularity. CoRR Yin Cui, Zeqi Gu, Dhruv Mahajan, Laurens van der Maaten, Serge J. Belongie, Ser-Nam Lim
2019	A*	`conf`	PHYRE: A New Benchmark for Physical Reasoning. NeurIPS Anton Bakhtin, Laurens van der Maaten, Justin Johnson, Laura Gustafson, Ross B. Girshick
2019	J	`jnl`	PHYRE: A New Benchmark for Physical Reasoning. CoRR Anton Bakhtin, Laurens van der Maaten, Justin Johnson, Laura Gustafson, Ross B. Girshick
2019	J	`jnl`	Privacy-Preserving Contextual Bandits. CoRR Awni Y. Hannun, Brian Knott, Shubho Sengupta, Laurens van der Maaten
2019	J	`jnl`	Self-Supervised Learning of Pretext-Invariant Representations. CoRR Ishan Misra, Laurens van der Maaten
2019	J	`jnl`	SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning. CoRR Yan Wang, Wei-Lun Chao, Kilian Q. Weinberger, Laurens van der Maaten
2018	A*	`conf`	3D Semantic Segmentation With Submanifold Sparse Convolutional Networks. CVPR Benjamin Graham, Martin Engelcke, Laurens van der Maaten
2018	J	`jnl`	Anytime Stereo Image Depth Estimation on Mobile Devices. CoRR Yan Wang, Zihang Lai, Gao Huang, Brian H. Wang, Laurens van der Maaten, Mark Campbell, Kilian Q. Weinberger
2018	A*	`conf`	CondenseNet: An Efficient DenseNet Using Learned Group Convolutions. CVPR Gao Huang, Shichen Liu, Laurens van der Maaten, Kilian Q. Weinberger
2018	—	`conf`	Countering Adversarial Images using Input Transformations. ICLR (Poster) Chuan Guo, Mayank Rana, Moustapha Cissé, Laurens van der Maaten
2018	—	`conf`	Exploring the Limits of Weakly Supervised Pretraining. ECCV (2) Dhruv Mahajan, Ross B. Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, Ashwin Bharambe, Laurens van der Maaten
2018	J	`jnl`	Exploring the Limits of Weakly Supervised Pretraining. CoRR Dhruv Mahajan, Ross B. Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, Ashwin Bharambe, Laurens van der Maaten
2018	J	`jnl`	Feature Denoising for Improving Adversarial Robustness. CoRR Cihang Xie, Yuxin Wu, Laurens van der Maaten, Alan L. Yuille, Kaiming He
2018	A*	`conf`	Learning by Asking Questions. CVPR Ishan Misra, Ross B. Girshick, Rob Fergus, Martial Hebert, Abhinav Gupta, Laurens van der Maaten
2018	—	`conf`	Multi-Scale Dense Networks for Resource Efficient Image Classification. ICLR Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, Kilian Q. Weinberger
2018	J	`jnl`	Multivariate Time-Series Classification Using the Hidden-Unit Logistic Model. IEEE Trans. Neural Networks Learn. Syst. Wenjie Pei, Hamdi Dibeklioglu, David M. J. Tax, Laurens van der Maaten
2018	—	`conf`	PAWE: Polysemy Aware Word Embeddings. ICISDM Taygun Kekeç, Laurens van der Maaten, David M. J. Tax
2018	A*	`conf`	Separating Self-Expression and Visual Content in Hashtag Supervision. CVPR Andreas Veit, Maximilian Nickel, Serge J. Belongie, Laurens van der Maaten
2017	J	`jnl`	3D Semantic Segmentation with Submanifold Sparse Convolutional Networks. CoRR Benjamin Graham, Martin Engelcke, Laurens van der Maaten
2017	J	`jnl`	Approximated and User Steerable tSNE for Progressive Visual Analytics. IEEE Trans. Vis. Comput. Graph. Nicola Pezzotti, Boudewijn P. F. Lelieveldt, Laurens van der Maaten, Thomas Höllt, Elmar Eisemann, Anna Vilanova
2017	A*	`conf`	CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning. CVPR Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Li Fei-Fei, C. Lawrence Zitnick, Ross B. Girshick
2017	J	`jnl`	CondenseNet: An Efficient DenseNet using Learned Group Convolutions. CoRR Gao Huang, Shichen Liu, Laurens van der Maaten, Kilian Q. Weinberger
2017	J	`jnl`	Countering Adversarial Images using Input Transformations. CoRR Chuan Guo, Mayank Rana, Moustapha Cissé, Laurens van der Maaten
2017	A*	`conf`	Densely Connected Convolutional Networks. CVPR Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger
2017	A*	`conf`	Inferring and Executing Programs for Visual Reasoning. ICCV Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Judy Hoffman, Li Fei-Fei, C. Lawrence Zitnick, Ross B. Girshick
2017	J	`jnl`	Inferring and Executing Programs for Visual Reasoning. CoRR Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Judy Hoffman, Li Fei-Fei, C. Lawrence Zitnick, Ross B. Girshick
2017	A*	`conf`	Learning Visual N-Grams from Web Data. ICCV Ang Li, Allan Jabri, Armand Joulin, Laurens van der Maaten
2017	J	`jnl`	Learning by Asking Questions. CoRR Ishan Misra, Ross B. Girshick, Rob Fergus, Martial Hebert, Abhinav Gupta, Laurens van der Maaten
2017	J	`jnl`	Memory-Efficient Implementation of DenseNets. CoRR Geoff Pleiss, Danlu Chen, Gao Huang, Tongcheng Li, Laurens van der Maaten, Kilian Q. Weinberger
2017	J	`jnl`	Multi-Scale Dense Convolutional Networks for Efficient Prediction. CoRR Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, Kilian Q. Weinberger
2017	J	`jnl`	Separating Self-Expression and Visual Content in Hashtag Supervision. CoRR Andreas Veit, Maximilian Nickel, Serge J. Belongie, Laurens van der Maaten
2017	J	`jnl`	Submanifold Sparse Convolutional Networks. CoRR Benjamin Graham, Laurens van der Maaten
2016	J	`jnl`	CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning. CoRR Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Li Fei-Fei, C. Lawrence Zitnick, Ross B. Girshick
2016	—	`conf`	Learning Visual Features from Large Weakly Supervised Data. ECCV (7) Armand Joulin, Laurens van der Maaten, Allan Jabri, Nicolas Vasilache
2016	J	`jnl`	Learning Visual N-Grams from Web Data. CoRR Ang Li, Allan Jabri, Armand Joulin, Laurens van der Maaten
2016	J	`jnl`	Modeling Time Series Similarity with Siamese Recurrent Networks. CoRR Wenjie Pei, David M. J. Tax, Laurens van der Maaten
2016	J	`jnl`	Persistent self-supervised learning principle: from stereo to monocular vision for obstacle avoidance. CoRR Kevin van Hecke, Guido de Croon, Laurens van der Maaten, Daniel Hennes, Dario Izzo
2016	—	`conf`	Revisiting Visual Question Answering Baselines. ECCV (8) Allan Jabri, Armand Joulin, Laurens van der Maaten
2016	J	`jnl`	Revisiting Visual Question Answering Baselines. CoRR Allan Jabri, Armand Joulin, Laurens van der Maaten
2015	J	`jnl`	Adaptive stereo similarity fusion using confidence measures. Comput. Vis. Image Underst. Gorkem Saygili, Laurens van der Maaten, Emile A. Hendriks
2015	J	`jnl`	Approximated and User Steerable tSNE for Progressive Visual Analytics. CoRR Nicola Pezzotti, Boudewijn P. F. Lelieveldt, Laurens van der Maaten, Thomas Höllt, Elmar Eisemann, Anna Vilanova
2015	J	`jnl`	Automatic Thread-Level Canvas Analysis: A machine-learning approach to analyzing the canvas of paintings. IEEE Signal Process. Mag. Laurens van der Maaten, Robert G. Erdmann
2015	J	`jnl`	Introduction to the special issue on visual analytics using multidimensional projections. Neurocomputing Michaël Aupetit, Laurens van der Maaten
2015	J	`jnl`	Learning Visual Features from Large Weakly Supervised Data. CoRR Armand Joulin, Laurens van der Maaten, Allan Jabri, Nicolas Vasilache
2015	J	`jnl`	Time Series Classification using the Hidden-Unit Logistic Model. CoRR Wenjie Pei, Hamdi Dibeklioglu, David M. J. Tax, Laurens van der Maaten
2014	J	`jnl`	Accelerating t-SNE using tree-based algorithms. J. Mach. Learn. Res. Laurens van der Maaten
2014	B	`conf`	Graph-Based Kinship Recognition. ICPR Yuanhao Guo, Hamdi Dibeklioglu, Laurens van der Maaten
2014	B	`conf`	Hybrid Kinect Depth Map Refinement for Transparent Objects. ICPR Gorkem Saygili, Laurens van der Maaten, Emile A. Hendriks
2014	B	`conf`	Improving Object Tracking by Adapting Detectors. ICPR Lu Zhang, Laurens van der Maaten
2014	J	`jnl`	Marginalizing Corrupted Features. CoRR Laurens van der Maaten, Minmin Chen, Stephen Tyree, Kilian Q. Weinberger
2014	—	`conf`	On Fast Trackers that are Robust to Partial Occlusions. CVPR Workshops Lu Zhang, Hamdi Dibeklioglu, Laurens van der Maaten
2014	J	`jnl`	Preserving Structure in Model-Free Tracking. IEEE Trans. Pattern Anal. Mach. Intell. Lu Zhang, Laurens van der Maaten
2014	A*	`conf`	Speeding Up Tracking by Ignoring Features. CVPR Lu Zhang, Hamdi Dibeklioglu, Laurens van der Maaten
2014	B	`conf`	Stereo Similarity Metric Fusion Using Stereo Confidence. ICPR Gorkem Saygili, Laurens van der Maaten, Emile A. Hendriks
2013	—	`ed.`	1st International Workshop on Visual Analytics Using Multidimensional Projections, VAMP@EuroVis 2013, Leipzig, Germany, June 19, 2013 VAMP@EuroVis Michaël Aupetit, Laurens van der Maaten
2013	A*	`conf`	Barnes-Hut-SNE ICLR Laurens van der Maaten
2013	J	`jnl`	Divvy: fast and intuitive exploratory data analysis. J. Mach. Learn. Res. Joshua M. Lewis, Virginia R. de Sa, Laurens van der Maaten
2013	—	`conf`	Learning with Marginalized Corrupted Features. ICML (1) Laurens van der Maaten, Minmin Chen, Stephen Tyree, Kilian Q. Weinberger
2013	A*	`conf`	Structure Preserving Object Tracking. CVPR Lu Zhang, Laurens van der Maaten
2012	B	`conf`	A Behavioral Investigation of Dimensionality Reduction. CogSci Joshua M. Lewis, Laurens van der Maaten, Virginia R. de Sa
2012	B	`conf`	Accelerating Cost Aggregation for Real-Time Stereo Matching. ICPADS Jianbin Fang, Ana Lucia Varbanescu, Jie Shen, Henk J. Sips, Gorkem Saygili, Laurens van der Maaten
2012	J	`jnl`	Action unit classification using active appearance models and conditional random fields. Cogn. Process. Laurens van der Maaten, Emile A. Hendriks
2012	J	`jnl`	Analyzing floristic inventories with multiple maps. Ecol. Informatics Laurens van der Maaten, Sebastian Schmidtlein, Miguel D. Mahecha
2012	B	`conf`	Audio-visual emotion challenge 2012: a simple approach. ICMI Laurens van der Maaten
2012	B	`conf`	Improving segment based stereo matching using SURF key points. ICIP Gorkem Saygili, Laurens van der Maaten, Emile A. Hendriks
2012	—	`conf`	Stochastic triplet embedding. MLSP Laurens van der Maaten, Kilian Q. Weinberger
2012	J	`jnl`	Visualizing non-metric similarities in multiple maps. Mach. Learn. Laurens van der Maaten, Geoffrey E. Hinton
2011	A	`conf`	Discussion of "Spectral Dimensionality Reduction via Maximum Entropy". AISTATS Laurens van der Maaten
2011	A	`conf`	Hidden-Unit Conditional Random Fields. AISTATS Laurens van der Maaten, Max Welling, Lawrence K. Saul
2011	A*	`conf`	Learning Discriminative Fisher Kernels. ICML Laurens van der Maaten
2010	—	`conf`	Capturing appearance variation in active appearance models. CVPR Workshops Laurens van der Maaten, Emile A. Hendriks
2010	A*	`conf`	Deep Supervised t-Distributed Embedding. ICML Martin Renqiang Min, Laurens van der Maaten, Zineng Yuan, Anthony J. Bonner, Zhaolei Zhang
2010	—	`conf`	Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development. NIPS Diane Hu, Laurens van der Maaten, Youngmin Cho, Lawrence K. Saul, Sorin Lerner
2010	—	`conf`	On Herding and the Perceptron Cycling Theorem. NIPS Andrew Gelfand, Yutian Chen, Laurens van der Maaten, Max Welling
2009	A	`conf`	Learning a Parametric Embedding by Preserving Local Structure. AISTATS Laurens van der Maaten
2007	—	`conf`	Off-Line Learning with Transductive Confidence Machines: An Empirical Evaluation. MLDM Stijn Vanderlooy, Laurens van der Maaten, Ida G. Sprinkhuizen-Kuyper
2005	—	`conf`	Improving automatic writer identification. BNAIC Laurens van der Maaten, Eric O. Postma