Hanlin Goh

According to our database, Hanlin Goh authored at least 37 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Label-Efficient Sleep Staging Using Transformers Pre-trained with Position Prediction.

Sayeri Lala, Hanlin Goh, Christopher M. Sandino

CoRR, 2024

Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization.

Yuhang Zang, Hanlin Goh, Joshua M. Susskind, Chen Huang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures.

Vimal Thilak, Chen Huang, Omid Saremi, Laurent Dinh, Hanlin Goh, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Frequency-Aware Masked Autoencoders for Multimodal Pretraining on Biosignals.

Ran Liu, Ellen L. Zippi, Hadi Pouransari, Christopher M. Sandino, Jingping Nie, Hanlin Goh, Erdrin Azemi, Ali Moin

CoRR, 2023

MAST: Masked Augmentation Subspace Training for Generalizable Self-Supervised Priors.

Chen Huang, Hanlin Goh, Jiatao Gu, Joshua M. Susskind

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

MAEEG: Masked Auto-encoder for EEG Representation Learning.

Hsiang-Yun Sherry Chien, Hanlin Goh, Christopher M. Sandino, Joseph Y. Cheng

CoRR, 2022

Towards Multimodal Multitask Scene Understanding Models for Indoor Mobile Agents.

Yao-Hung Hubert Tsai, Hanlin Goh, Ali Farhadi, Jian Zhang

CoRR, 2022

GAUDI: A Neural Architect for Immersive 3D Scene Generation.

Miguel Ángel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott, Alexander Toshev, Zhuoyuan Chen, Laurent Dinh, Shuangfei Zhai, Hanlin Goh, Daniel Ulbricht, Afshin Dehghan, Joshua M. Susskind

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Position Prediction as an Effective Pretraining Strategy.

Shuangfei Zhai, Navdeep Jaitly, Jason Ramapuram, Dan Busbridge, Tatiana Likhomanenko, Joseph Y. Cheng, Walter Talbott, Chen Huang, Hanlin Goh, Joshua M. Susskind

Proceedings of the International Conference on Machine Learning, 2022

2021

Implicit Acceleration and Feature Learning in Infinitely Wide Neural Networks with Bottlenecks.

Etai Littwin, Omid Saremi, Shuangfei Zhai, Vimal Thilak, Hanlin Goh, Joshua M. Susskind, Greg Yang

CoRR, 2021

An Attention Free Transformer.

Shuangfei Zhai, Walter Talbott, Nitish Srivastava, Chen Huang, Hanlin Goh, Ruixiang Zhang, Josh M. Susskind

CoRR, 2021

Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning.

Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Subject-Aware Contrastive Learning for Biosignals.

Joseph Y. Cheng, Hanlin Goh, Kaan Dogrusoz, Oncel Tuzel, Erdrin Azemi

CoRR, 2020

Capsules with Inverted Dot-Product Attention Routing.

Yao-Hung Hubert Tsai, Nitish Srivastava, Hanlin Goh, Ruslan Salakhutdinov

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Geometric Capsule Autoencoders for 3D Point Clouds.

Nitish Srivastava, Hanlin Goh, Ruslan Salakhutdinov

CoRR, 2019

2017

DeepHash for Image Instance Retrieval: Getting Regularization, Depth and Fine-Tuning Right.

Jie Lin, Olivier Morère, Antoine Veillard, Ling-Yu Duan, Hanlin Goh, Vijay Chandrasekhar

Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval, 2017

2016

A practical guide to CNNs and Fisher Vectors for image instance retrieval.

Vijay Chandrasekhar, Jie Lin, Olivier Morère, Hanlin Goh, Antoine Veillard

Signal Process., 2016

2015

DeepHash: Getting Regularization, Depth and Fine-Tuning Right.

Jie Lin, Olivier Morère, Vijay Chandrasekhar, Antoine Veillard, Hanlin Goh

CoRR, 2015

Co-regularized deep representations for video summarization.

Olivier Morère, Hanlin Goh, Antoine Veillard, Vijay Chandrasekhar, Jie Lin

Proceedings of the 2015 IEEE International Conference on Image Processing, 2015

Compact Global Descriptors for Visual Search.

Vijay Chandrasekhar, Jie Lin, Olivier Morère, Antoine Veillard, Hanlin Goh

Proceedings of the 2015 Data Compression Conference, 2015

2014

Learning Deep Hierarchical Visual Feature Coding.

Hanlin Goh, Nicolas Thome, Matthieu Cord, Joo-Hwee Lim

IEEE Trans. Neural Networks Learn. Syst., 2014

Understanding the Nature of First-Person Videos: Characterization and Classification Using Low-Level Features.

Cheston Tan, Hanlin Goh, Vijay Chandrasekhar, Liyuan Li, Joo-Hwee Lim

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013

Learning Deep Visual Representations. (Apprentissage de Repre'sentations Visuelles Profondes).

Hanlin Goh

PhD thesis, 2013

Top-Down Regularization of Deep Belief Networks.

Hanlin Goh, Nicolas Thome, Matthieu Cord, Joo-Hwee Lim

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012

Unsupervised and Supervised Visual Codes with Restricted Boltzmann Machines.

Hanlin Goh, Nicolas Thome, Matthieu Cord, Joo-Hwee Lim

Proceedings of the Computer Vision - ECCV 2012, 2012

2011

Learning invariant color features with sparse topographic restricted Boltzmann machines.

Hanlin Goh, Lukasz Kusmierz, Joo-Hwee Lim, Nicolas Thome, Matthieu Cord

Proceedings of the 18th IEEE International Conference on Image Processing, 2011

2009

Fuzzy Associative Conjuncted Maps Network.

Hanlin Goh, Joo-Hwee Lim, Chai Quek

IEEE Trans. Neural Networks, 2009

I2R ImageCLEF Photo Annotation 2009 Working Notes.

Jiquan Ngiam, Hanlin Goh

Proceedings of the Working Notes for CLEF 2009 Workshop co-located with the 13th European Conference on Digital Libraries (ECDL 2009) , Corfù, Greece, September 30, 2009

Learning Global and Regional Features for Photo Annotation.

Jiquan Ngiam, Hanlin Goh

Proceedings of the Multilingual Information Access Evaluation II. Multimedia Experiments, 2009

Learning from an ensemble of Receptive Fields.

Hanlin Goh, Joo Hwe Lim, Chai Quek

Proceedings of the 8th IEEE International Conference on Cognitive Informatics, 2009

2008

Bi-modal Conceptual Indexing for Medical Image Retrieval.

Joo-Hwee Lim, Jean-Pierre Chevallet, Diem Thi Hoang Le, Hanlin Goh

Proceedings of the Advances in Multimedia Modeling, 2008

Learning associations of conjuncted fuzzy sets for data prediction.

Hanlin Goh, Joo-Hwee Lim, Chai Quek

Proceedings of the International Joint Conference on Neural Networks, 2008

Exact integral images at generic angles for 2D barcode detection.

Tat-Jun Chin, Hanlin Goh, Ngan Meng Tan

Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

Cascaded classification with optimal candidate selection for effective place recognition.

Yiqun Li, Joo-Hwee Lim, Hanlin Goh

Proceedings of the 2008 IEEE International Conference on Multimedia and Expo, 2008

Using densely recorded scenes for place recognition.

Tat-Jun Chin, Hanlin Goh, Joo-Hwee Lim

Proceedings of the IEEE International Conference on Acoustics, 2008

Boosting descriptors condensed from video sequences for place recognition.

Tat-Jun Chin, Hanlin Goh, Joo-Hwee Lim

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2008

2007

An image-based outdoor place recognition and information retrieval system.

Hanlin Goh, Yiqun Li, Joo-Hwee Lim

Proceedings of the 15th International Conference on Multimedia 2007, 2007