An image-based outdoor place recognition and information retrieval system. - Hanlin Goh; Yiqun Li; Joo-Hwee Lim (ACM Multimedia, 2007)

Boosting descriptors condensed from video sequences for place recognition. - Tat-Jun Chin; Hanlin Goh; Joo-Hwee Lim (CVPR Workshops, 2008)

Using densely recorded scenes for place recognition. - Tat-Jun Chin; Hanlin Goh; Joo-Hwee Lim (ICASSP, 2008)

Cascaded classification with optimal candidate selection for effective place recognition. - Yiqun Li; Joo-Hwee Lim; Hanlin Goh (ICME, 2008)

Exact integral images at generic angles for 2D barcode detection. - Tat-Jun Chin; Hanlin Goh; Ngan Meng Tan (ICPR, 2008)

Learning associations of conjuncted fuzzy sets for data prediction. - Hanlin Goh; Joo-Hwee Lim; Chai Quek (IJCNN, 2008)

Bi-modal Conceptual Indexing for Medical Image Retrieval. - Joo-Hwee Lim; Jean-Pierre Chevallet; Diem Thi Hoang Le; Hanlin Goh (MMM, 2008)

Learning from an ensemble of Receptive Fields. - Hanlin Goh; Joo Hwe Lim; Chai Quek (IEEE ICCI, 2009)

Learning Global and Regional Features for Photo Annotation. - Jiquan Ngiam; Hanlin Goh (CLEF (2), 2009)

I2R ImageCLEF Photo Annotation 2009 Working Notes. - Jiquan Ngiam; Hanlin Goh (CLEF (Working Notes), 2009)

Fuzzy Associative Conjuncted Maps Network. - Hanlin Goh; Joo-Hwee Lim; Chai Quek (IEEE Trans. Neural Networks, 2009)

Learning invariant color features with sparse topographic restricted Boltzmann machines. - Hanlin Goh; Lukasz Kusmierz; Joo-Hwee Lim; Nicolas Thome; Matthieu Cord (ICIP, 2011)

Unsupervised and Supervised Visual Codes with Restricted Boltzmann Machines. - Hanlin Goh; Nicolas Thome; Matthieu Cord; Joo-Hwee Lim (ECCV (5), 2012)

Top-Down Regularization of Deep Belief Networks. - Hanlin Goh; Nicolas Thome; Matthieu Cord; Joo-Hwee Lim (NIPS, 2013)

Learning Deep Visual Representations. (Apprentissage de Repre'sentations Visuelles Profondes). - Hanlin Goh (2013)

Understanding the Nature of First-Person Videos: Characterization and Classification Using Low-Level Features. - Cheston Tan; Hanlin Goh; Vijay Chandrasekhar 001; Liyuan Li; Joo-Hwee Lim (CVPR Workshops, 2014)

Learning Deep Hierarchical Visual Feature Coding. - Hanlin Goh; Nicolas Thome; Matthieu Cord; Joo-Hwee Lim (IEEE Trans. Neural Networks Learn. Syst., 2014)

Compact Global Descriptors for Visual Search. - Vijay Chandrasekhar 001; Jie Lin 001; Olivier Morère; Antoine Veillard; Hanlin Goh (DCC, 2015)

Co-regularized deep representations for video summarization. - Olivier Morère; Hanlin Goh; Antoine Veillard; Vijay Chandrasekhar 001; Jie Lin 001 (ICIP, 2015)

DeepHash: Getting Regularization, Depth and Fine-Tuning Right. - Jie Lin 001; Olivier Morère; Vijay Chandrasekhar 001; Antoine Veillard; Hanlin Goh (CoRR, 2015)

A practical guide to CNNs and Fisher Vectors for image instance retrieval. - Vijay Chandrasekhar 001; Jie Lin 001; Olivier Morère; Hanlin Goh; Antoine Veillard (Signal Process., 2016)

DeepHash for Image Instance Retrieval: Getting Regularization, Depth and Fine-Tuning Right. - Jie Lin 001; Olivier Morère; Antoine Veillard; Ling-Yu Duan; Hanlin Goh; Vijay Chandrasekhar 001 (ICMR, 2017)

Geometric Capsule Autoencoders for 3D Point Clouds. - Nitish Srivastava; Hanlin Goh; Ruslan Salakhutdinov (CoRR, 2019)

Capsules with Inverted Dot-Product Attention Routing. - Yao-Hung Hubert Tsai; Nitish Srivastava; Hanlin Goh; Ruslan Salakhutdinov (ICLR, 2020)

Subject-Aware Contrastive Learning for Biosignals. - Joseph Y. Cheng; Hanlin Goh; Kaan Dogrusoz; Oncel Tuzel; Erdrin Azemi (CoRR, 2020)

Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning. - Yue Wu 001; Shuangfei Zhai; Nitish Srivastava; Joshua M. Susskind; Jian Zhang 050; Ruslan Salakhutdinov; Hanlin Goh (ICML, 2021)

An Attention Free Transformer. - Shuangfei Zhai; Walter Talbott; Nitish Srivastava; Chen Huang 001; Hanlin Goh; Ruixiang Zhang; Josh M. Susskind (CoRR, 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)

Position Prediction as an Effective Pretraining Strategy. - Shuangfei Zhai; Navdeep Jaitly; Jason Ramapuram; Dan Busbridge; Tatiana Likhomanenko; Joseph Y. Cheng; Walter Talbott; Chen Huang 001; Hanlin Goh; Joshua M. Susskind (ICML, 2022)

GAUDI: A Neural Architect for Immersive 3D Scene Generation. - Miguel Ángel Bautista 001; Pengsheng Guo; Samira Abnar; Walter Talbott; Alexander Toshev; Zhuoyuan Chen; Laurent Dinh; Shuangfei Zhai; Hanlin Goh; Daniel Ulbricht; Afshin Dehghan; Joshua M. Susskind (NeurIPS, 2022)

Towards Multimodal Multitask Scene Understanding Models for Indoor Mobile Agents. - Yao-Hung Hubert Tsai; Hanlin Goh; Ali Farhadi; Jian Zhang 050 (CoRR, 2022)

MAEEG: Masked Auto-encoder for EEG Representation Learning. - Hsiang-Yun Sherry Chien; Hanlin Goh; Christopher M. Sandino; Joseph Y. Cheng (CoRR, 2022)

MAST: Masked Augmentation Subspace Training for Generalizable Self-Supervised Priors. - Chen Huang 001; Hanlin Goh; Jiatao Gu; Joshua M. Susskind (ICLR, 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)

LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures. - Vimal Thilak; Chen Huang 001; Omid Saremi; Laurent Dinh; Hanlin Goh; Preetum Nakkiran; Joshua M. Susskind; Etai Littwin (ICLR, 2024)

Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization. - Yuhang Zang; Hanlin Goh; Joshua M. Susskind; Chen Huang 001 (ICLR, 2024)

Label-Efficient Sleep Staging Using Transformers Pre-trained with Position Prediction. - Sayeri Lala; Hanlin Goh; Christopher M. Sandino (CoRR, 2024)

How PARTs assemble into wholes: Learning the relative composition of images. - Melika Ayoughi; Samira Abnar; Chen Huang 001; Christopher Michael Sandino; Sayeri Lala; Eeshan Gunesh Dhekane; Dan Busbridge; Shuangfei Zhai; Vimal Thilak; Joshua M. Susskind; Pascal Mettes; Paul Groth; et al. (CoRR, 2025)