Jiquan Ngiam
Jiquan Ngiam
Google Brain
Verified email at google.com - Homepage
Cited by
Cited by
Multimodal deep learning
J Ngiam, A Khosla, M Kim, J Nam, H Lee, AY Ng
ICML, 2011
On optimization methods for deep learning
QV Le, J Ngiam, A Coates, A Lahiri, B Prochnow, AY Ng
ICML, 2011
Gpipe: Efficient training of giant neural networks using pipeline parallelism
Y Huang, Y Cheng, A Bapna, O Firat, D Chen, M Chen, HJ Lee, J Ngiam, ...
Advances in neural information processing systems 32, 103-112, 2019
Scalability in perception for autonomous driving: Waymo open dataset
P Sun, H Kretzschmar, X Dotiwalla, A Chouard, V Patnaik, P Tsui, J Guo, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
Tiled convolutional neural networks
J Ngiam, Z Chen, D Chia, P Koh, Q Le, A Ng
Advances in neural information processing systems 23, 2010
ICA with reconstruction cost for efficient overcomplete feature learning
Q Le, A Karpenko, J Ngiam, A Ng
Advances in neural information processing systems 24, 1017-1025, 2011
Sparse filtering
J Ngiam, Z Chen, S Bhaskar, P Koh, A Ng
Advances in neural information processing systems 24, 1125-1133, 2011
Learning deep energy models
J Ngiam, Z Chen, PW Koh, AY Ng
ICML, 2011
Condconv: Conditionally parameterized convolutions for efficient inference
B Yang, G Bender, QV Le, J Ngiam
arXiv preprint arXiv:1904.04971, 2019
End-to-end multi-view fusion for 3d object detection in lidar point clouds
Y Zhou, P Sun, Y Zhang, D Anguelov, J Gao, T Ouyang, J Guo, J Ngiam, ...
Conference on Robot Learning, 923-932, 2020
A Classification-Based Polyphonic Piano Transcription Approach Using Learned Feature Representations.
J Nam, J Ngiam, H Lee, M Slaney
Ismir, 175-180, 2011
UFLDL tutorial
A Ng, J Ngiam, CY Foo, Y Mai, C Suen
Computer Science Department, Stanford University. http://deeplearning …, 2010
Domain adaptive transfer learning with specialist models
J Ngiam, D Peng, V Vasudevan, S Kornblith, QV Le, R Pang
arXiv preprint arXiv:1811.07056, 2018
Experience is a double-edged sword: A computational model of the encoding/retrieval trade-off with familiarity
LM Reder, C Paynter, RA Diana, J Ngiam, D Dickison
Psychology of learning and motivation 48, 271-312, 2007
Starnet: Targeted computation for object detection in point clouds
J Ngiam, B Caine, W Han, B Yang, Y Chai, P Sun, Y Zhou, X Yi, O Alsharif, ...
arXiv preprint arXiv:1908.11069, 2019
The psychology of learning and motivation
SK Reed, JA Johnsen, C Bower
Deep learning
A Ng, J Ngiam, CY Foo, Y Mai
CS229 Lecture Notes, 1-30, 2014
Improving 3d object detection through progressive population based augmentation
S Cheng, Z Leng, ED Cubuk, B Zoph, C Bai, J Ngiam, Y Song, B Caine, ...
European Conference on Computer Vision, 279-294, 2020
Using videos to evaluate image model robustness
K Gu, B Yang, J Ngiam, Q Le, J Shlens
arXiv preprint arXiv:1904.10076, 2019
Unsupervised feature learning and deep learning
A Ng, J Ngiam, CY Foo, Y Mai, C Suen, A Coates, A Maas, A Hannun, ...
Technical report, Stanford University, 2013
The system can't perform the operation now. Try again later.
Articles 1–20