Lee, Honglak

181 publications

TMLR 2026 Towards Scalable Language-Image Pre-Training for 3D Medical Imaging Chenhui Zhao, Yiwei Lyu, Asadur Zaman Chowdury, Edward S Harake, Akhil Kondepudi, Akshay T Rao, Xinhai Hou, Honglak Lee, Todd C Hollon
AAAI 2025 3D Denoisers Are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation Sungjun Cho, Dae-Woong Jeong, Sung Moon Ko, Jinwoo Kim, Sehui Han, Seunghoon Hong, Honglak Lee, Moontae Lee
NeurIPS 2025 Active Test-Time Vision-Language Navigation Heeju Ko, Sungjune Kim, Gyeongrok Oh, Jeongyoon Yoon, Honglak Lee, Sujin Jang, Seungryong Kim, Sangpil Kim
NeurIPS 2025 KL Penalty Control via Perturbation for Direct Preference Optimization Sangkyu Lee, Janghoon Han, Hosung Song, Stanley Jungkyu Choi, Honglak Lee, Youngjae Yu
NeurIPS 2025 MLRC-Bench: Can Language Agents Solve Machine Learning Research Challenges? Yunxiang Zhang, Muhammad Khalifa, Shitanshu Bhushan, Grant D Murphy, Lajanugen Logeswaran, Jaekyeom Kim, Moontae Lee, Honglak Lee, Lu Wang
ICML 2025 Probing Visual Language Priors in VLMs Tiange Luo, Ang Cao, Gunhee Lee, Justin Johnson, Honglak Lee
CVPR 2025 Scalable Video-to-Dataset Generation for Cross-Platform Mobile Agents Yunseok Jang, Yeda Song, Sungryull Sohn, Lajanugen Logeswaran, Tiange Luo, Dong-Ki Kim, Kyunghoon Bae, Honglak Lee
AAAI 2025 Step-Calibrated Diffusion for Biomedical Optical Image Restoration Yiwei Lyu, Sung Jik Cha, Cheng Jiang, Asadur Zaman Chowdury, Xinhai Hou, Edward S. Harake, Akhil Kondepudi, Christian W. Freudiger, Honglak Lee, Todd C. Hollon
ICLR 2025 Subtask-Aware Visual Reward Learning from Segmented Demonstrations Changyeon Kim, Minho Heo, Doohyun Lee, Honglak Lee, Jinwoo Shin, Joseph J Lim, Kimin Lee
ICCV 2025 Visual Test-Time Scaling for GUI Agent Grounding Tiange Luo, Lajanugen Logeswaran, Justin Johnson, Honglak Lee
NeurIPSW 2024 A Self-Supervised Framework for Learning Whole Slide Representations Xinhai Hou, Cheng Jiang, Akhil Kondepudi, Yiwei Lyu, Asadur Zaman Chowdury, Honglak Lee, Todd C Hollon
NeurIPSW 2024 An Empirical Study of CLIP Fine-Tuning with Similarity Clusters Shixuan Liu, Yiwei Lyu, Honglak Lee, Todd C Hollon
NeurIPS 2024 AutoGuide: Automated Generation and Selection of Context-Aware Guidelines for Large Language Model Agents Yao Fu, Dong-Ki Kim, Jaekyeom Kim, Sungryull Sohn, Lajanugen Logeswaran, Kyunghoon Bae, Honglak Lee
ICMLW 2024 AutoGuide: Automated Generation and Selection of Context-Aware Guidelines for Large Language Model Agents Yao Fu, Dong-Ki Kim, Jaekyeom Kim, Sungryull Sohn, Lajanugen Logeswaran, Kyunghoon Bae, Honglak Lee
ICML 2024 Degeneration-Free Policy Optimization: RL Fine-Tuning for Language Models Without Degeneration Youngsoo Jang, Geon-Hyeong Kim, Byoungjip Kim, Yu Jin Kim, Honglak Lee, Moontae Lee
AAAI 2024 Learning to Unlearn: Instance-Wise Unlearning for Pre-Trained Classifiers Sungmin Cha, Sungjun Cho, Dasol Hwang, Honglak Lee, Taesup Moon, Moontae Lee
NeurIPSW 2024 Mobile OS Task Procedure Extraction from YouTube Yunseok Jang, Yeda Song, Sungryull Sohn, Lajanugen Logeswaran, Tiange Luo, Honglak Lee
CVPRW 2024 NICE: CVPR 2023 Challenge on Zero-Shot Image Captioning Taehoon Kim, Pyunghwan Ahn, Sangyun Kim, Sihaeng Lee, Mark Marsden, Alessandra Sala, Seung Hwan Kim, Bohyung Han, Kyoung Mu Lee, Honglak Lee, Kyounghoon Bae, Xiangyu Wu, Yi Gao, Hailiang Zhang, Yang Yang, Weili Guo, Jianfeng Lu, Youngtaek Oh, Jae-Won Cho, Dong-Jin Kim, In So Kweon, Junmo Kim, Wooyoung Kang, Won Young Jhoo, Byungseok Roh, Jonghwan Mun, Solgil Oh, Kenan Emir Ak, Gwang-Gook Lee, Yan Xu, Mingwei Shen, Kyomin Hwang, Wonsik Shin, Kamin Lee, Wonhark Park, Dongkwan Lee, Nojun Kwak, Yujin Wang, Yimu Wang, Tiancheng Gu, Xingchang Lv, Mingmao Sun
CVPRW 2024 Show, Think, and Tell: Thought-Augmented Fine-Tuning of Large Language Models for Video Captioning Byoungjip Kim, Dasol Hwang, Sungjun Cho, Youngsoo Jang, Honglak Lee, Moontae Lee
ICMLW 2024 SkillAct: Using Skill Abstractions Improves LLM Agents Anthony Zhe Liu, Jongwook Choi, Sungryull Sohn, Yao Fu, Jaekyeom Kim, Dong-Ki Kim, Xinhe Wang, Jaewon Yoo, Honglak Lee
ICLRW 2024 Source-Aware Training Enables Knowledge Attribution in Language Models Muhammad Khalifa, David Wadden, Emma Strubell, Honglak Lee, Lu Wang, Iz Beltagy, Hao Peng
CVPRW 2024 Super-Resolution of Biomedical Volumes with 2D Supervision Cheng Jiang, Alexander Gedeon, Yiwei Lyu, Eric Landgraf, Yufeng Zhang, Xinhai Hou, Akhil Kondepudi, Asadur Chowdury, Honglak Lee, Todd C. Hollon
CoLLAs 2024 Towards More Diverse Evaluation of Class Incremental Learning: Representation Learning Perspective Sungmin Cha, Jihwan Kwak, Dongsub Shim, Hyunwoo Kim, Moontae Lee, Honglak Lee, Taesup Moon
AAAI 2024 Unsupervised Object Interaction Learning with Counterfactual Dynamics Models Jongwook Choi, Sungtae Lee, Xinyu Wang, Sungryull Sohn, Honglak Lee
ECCV 2024 View Selection for 3D Captioning via Diffusion Ranking Tiange Luo, Justin Johnson, Honglak Lee
ICLRW 2023 A Picture Is Worth a Thousand Words: Language Models Plan from Pixels Anthony Zhe Liu, Lajanugen Logeswaran, Sungryull Sohn, Honglak Lee
NeurIPS 2023 Combining Behaviors with the Successor Features Keyboard Wilka Carvalho Carvalho, Andre Saraiva, Angelos Filos, Andrew Lampinen, Loic Matthey, Richard L Lewis, Honglak Lee, Satinder P. Singh, Danilo Jimenez Rezende, Daniel Zoran
ICLR 2023 Composing Task Knowledge with Modular Successor Feature Approximators Wilka Torrico Carvalho, Angelos Filos, Richard Lewis, Honglak Lee, Satinder Singh
NeurIPS 2023 CycleNet: Rethinking Cycle Consistency in Text-Guided Diffusion for Image Manipulation Sihan Xu, Ziqiao Ma, Yidong Huang, Honglak Lee, Joyce Chai
WACV 2023 Enriched CNN-Transformer Feature Aggregation Networks for Super-Resolution Jinsu Yoo, Taehoon Kim, Sihaeng Lee, Seung Hwan Kim, Honglak Lee, Tae Hyun Kim
ICLRW 2023 Exploring Demonstration Ensembling for In-Context Learning Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
ICML 2023 Go Beyond Imagination: Maximizing Episodic Reachability with World Models Yao Fu, Run Peng, Honglak Lee
AAAI 2023 Grouping Matrix Based Graph Pooling with Adaptive Number of Clusters Sung Moon Ko, Sungjun Cho, Dae-Woong Jeong, Sehui Han, Moontae Lee, Honglak Lee
NeurIPS 2023 Guide Your Agent with Adaptive Multimodal Rewards Changyeon Kim, Younggyo Seo, Hao Liu, Lisa Lee, Jinwoo Shin, Honglak Lee, Kimin Lee
ICMLW 2023 Guide Your Agent with Adaptive Multimodal Rewards Changyeon Kim, Younggyo Seo, Hao Liu, Lisa Lee, Jinwoo Shin, Honglak Lee, Kimin Lee
ICMLW 2023 Hierarchical Decomposition Framework for Feasibility-Hard Combinatorial Optimization Hanbum Ko, Minu Kim, Han-Seul Jeong, Sunghoon Hong, Deunsol Yoon, Youngjoon Park, Woohyung Lim, Honglak Lee, Moontae Lee, Kanghoon Lee, Sungbin Lim, Sungryull Sohn
CVPR 2023 Hierarchical Discriminative Learning Improves Visual Representations of Biomedical Microscopy Cheng Jiang, Xinhai Hou, Akhil Kondepudi, Asadur Chowdury, Christian W. Freudiger, Daniel A. Orringer, Honglak Lee, Todd C. Hollon
AAAI 2023 Learning Compositional Tasks from Language Instructions Lajanugen Logeswaran, Wilka Carvalho, Honglak Lee
ICMLW 2023 Learning Higher Order Skills That Efficiently Compose Anthony Zhe Liu, Dong-Ki Kim, Sungryull Sohn, Honglak Lee
ICMLW 2023 Mixed-Curvature Transformers for Graph Representation Learning Sungjun Cho, Seunghyuk Cho, Sungwoo Park, Hankook Lee, Honglak Lee, Moontae Lee
ICLRW 2023 Multimodal Subtask Graph Generation from Instructional Videos Yunseok Jang, Sungryull Sohn, Lajanugen Logeswaran, Tiange Luo, Moontae Lee, Honglak Lee
TMLR 2023 Neural Shape Compiler: A Unified Framework for Transforming Between Text, Point Cloud, and Program Tiange Luo, Honglak Lee, Justin Johnson
ICLR 2023 Preference Transformer: Modeling Human Preferences Using Transformers for RL Changyeon Kim, Jongjin Park, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
NeurIPS 2023 Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models Sungik Choi, Hankook Lee, Honglak Lee, Moontae Lee
NeurIPSW 2023 Prospector: Improving LLM Agents with Self-Asking and Trajectory Ranking Byoungjip Kim, Youngsoo Jang, Lajanugen Logeswaran, Geon-Hyeong Kim, Yu Jin Kim, Honglak Lee, Moontae Lee
NeurIPSW 2023 Reasoning About Action Preconditions with Programs Lajanugen Logeswaran, Sungryull Sohn, Yiwei Lyu, Anthony Liu, Dong-Ki Kim, Dongsub Shim, Moontae Lee, Honglak Lee
NeurIPS 2023 SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations Youngsoo Jang, Geon-Hyeong Kim, Jongmin Lee, Sungryull Sohn, Byoungjip Kim, Honglak Lee, Moontae Lee
NeurIPS 2023 Scalable 3D Captioning with Pretrained Models Tiange Luo, Chris Rockwell, Honglak Lee, Justin Johnson
AAAI 2023 Simple and Effective Synthesis of Indoor 3D Scenes Jing Yu Koh, Harsh Agrawal, Dhruv Batra, Richard Tucker, Austin Waters, Honglak Lee, Yinfei Yang, Jason Baldridge, Peter Anderson
ICCV 2023 Story Visualization by Online Text Augmentation with Context Memory Daechul Ahn, Daneul Kim, Gwangmo Song, Seung Hwan Kim, Honglak Lee, Dongyeop Kang, Jonghyun Choi
NeurIPSW 2023 TOD-Flow: Modeling the Structure of Task-Oriented Dialogues Sungryull Sohn, Yiwei Lyu, Anthony Liu, Lajanugen Logeswaran, Dong-Ki Kim, Dongsub Shim, Honglak Lee
ICLRW 2023 Unsupervised Object Interaction Learning with Counterfactual Dynamics Models Jongwook Choi, Sungtae Lee, Xinyu Wang, Sungryull Sohn, Honglak Lee
NeurIPS 2022 CEDe: A Collection of Expert-Curated Datasets with Atom-Level Entity Annotations for Optical Chemical Structure Recognition Rodrigo Hormazabal, Changyoung Park, Soonyoung Lee, Sehui Han, Yeonsik Jo, Jaewan Lee, Ahra Jo, Seung Hwan Kim, Jaegul Choo, Moontae Lee, Honglak Lee
NeurIPSW 2022 Composing Task Knowledge with Modular Successor Feature Approximators Wilka Torrico Carvalho, Angelos Filos, Richard Lewis, Honglak Lee, Satinder Singh
NeurIPSW 2022 Dynamics-Augmented Decision Transformer for Offline Dynamics Generalization Changyeon Kim, Junsu Kim, Younggyo Seo, Kimin Lee, Honglak Lee, Jinwoo Shin
UAI 2022 Fast Inference and Transfer of Compositional Task Structures for Few-Shot Task Generalization Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Lyubing Qiang, Izzeddin Gur, Aleksandra Faust, Honglak Lee
CVPR 2022 L-Verse: Bidirectional Generation Between Image and Text Taehoon Kim, Gwangmo Song, Sihaeng Lee, Sangyun Kim, Yewon Seo, Soonyoung Lee, Seung Hwan Kim, Honglak Lee, Kyunghoon Bae
AAAI 2022 Learning Action Translator for Meta Reinforcement Learning on Sparse-Reward Tasks Yijie Guo, Qiucheng Wu, Honglak Lee
NeurIPSW 2022 Learning Exploration Policies with View-Based Intrinsic Rewards Yijie Guo, Yao Fu, Run Peng, Honglak Lee
NeurIPSW 2022 Learning Exploration Policies with View-Based Intrinsic Rewards Yijie Guo, Yao Fu, Run Peng, Honglak Lee
AAAI 2022 Learning Parameterized Task Structure for Generalization to Unseen Entities Anthony Z. Liu, Sungryull Sohn, Mahdi Qazwini, Honglak Lee
ICLR 2022 Lipschitz-Constrained Unsupervised Skill Discovery Seohong Park, Jongwook Choi, Jaekyeom Kim, Honglak Lee, Gunhee Kim
NeurIPS 2022 OpenSRH: Optimizing Brain Tumor Surgery Using Intraoperative Stimulated Raman Histology Cheng Jiang, Asadur Chowdury, Xinhai Hou, Akhil Kondepudi, Christian Freudiger, Kyle Conway, Sandra Camelo-Piragua, Daniel Orringer, Honglak Lee, Todd Hollon
ICML 2022 Path-Aware and Structure-Preserving Generation of Synthetically Accessible Molecules Juhwan Noh, Dae-Woong Jeong, Kiyoung Kim, Sehui Han, Moontae Lee, Honglak Lee, Yousung Jung
NeurIPS 2022 Pure Transformers Are Powerful Graph Learners Jinwoo Kim, Dat Nguyen, Seonwoo Min, Sungjun Cho, Moontae Lee, Honglak Lee, Seunghoon Hong
NeurIPSW 2022 ReSPack: A Large-Scale Rectilinear Steiner Tree Packing Data Generator and Benchmark Kanghoon Lee, Youngjoon Park, Han-Seul Jeong, Sunghoon Hong, Deunsol Yoon, Sungryull Sohn, Minu Kim, Hanbum Ko, Moontae Lee, Honglak Lee, Kyunghoon Kim, Euihyuk Kim, Seonggeon Cho, Jaesang Min, Woohyung Lim
ICLR 2022 SURF: Semi-Supervised Reward Learning with Data Augmentation for Feedback-Efficient Preference-Based Reinforcement Learning Jongjin Park, Younggyo Seo, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
NeurIPS 2022 Transferring Pre-Trained Multimodal Representations with Cross-Modal Similarity Matching Byoungjip Kim, Sungik Choi, Dasol Hwang, Moontae Lee, Honglak Lee
NeurIPS 2022 Transformers Meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost Sungjun Cho, Seonwoo Min, Jinwoo Kim, Moontae Lee, Honglak Lee, Seunghoon Hong
NeurIPS 2022 UniCLIP: Unified Framework for Contrastive Language-Image Pre-Training Janghyeon Lee, Jongsuk Kim, Hyounguk Shon, Bumsoo Kim, Seung Hwan Kim, Honglak Lee, Junmo Kim
ICLR 2021 $i$-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee
ICLR 2021 Batch Reinforcement Learning Through Continuation Method Yijie Guo, Shengyu Feng, Nicolas Le Roux, Ed Chi, Honglak Lee, Minmin Chen
CVPR 2021 Cross-Modal Contrastive Learning for Text-to-Image Generation Han Zhang, Jing Yu Koh, Jason Baldridge, Honglak Lee, Yinfei Yang
NeurIPS 2021 Environment Generation for Zero-Shot Compositional Reinforcement Learning Izzeddin Gur, Natasha Jaques, Yingjie Miao, Jongwook Choi, Manoj Tiwari, Honglak Lee, Aleksandra Faust
ICLR 2021 Evolving Reinforcement Learning Algorithms John D Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Quoc V Le, Sergey Levine, Honglak Lee, Aleksandra Faust
NeurIPSW 2021 Fast Inference and Transfer of Compositional Task for Few-Shot Task Generalization Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Lyubing Qiang, Izzeddin Gur, Aleksandra Faust, Honglak Lee
AAAI 2021 Improved Consistency Regularization for GANs Zhengli Zhao, Sameer Singh, Honglak Lee, Zizhao Zhang, Augustus Odena, Han Zhang
NeurIPS 2021 Improving Transferability of Representations via Augmentation-Aware Self-Supervision Hankook Lee, Kibok Lee, Kimin Lee, Honglak Lee, Jinwoo Shin
NeurIPSW 2021 Learning Action Translator for Meta Reinforcement Learning on Sparse-Reward Tasks Yijie Guo, Qiucheng Wu, Honglak Lee
NeurIPSW 2021 Learning Compositional Tasks from Language Instructions Lajanugen Logeswaran, Wilka Torrico Carvalho, Honglak Lee
NeurIPSW 2021 Learning Parameterized Task Structure for Generalization to Unseen Entities Anthony Zhe Liu, Sungryull Sohn, Mahdi Qazwini, Honglak Lee
ICML 2021 Learning to Weight Imperfect Demonstrations Yunke Wang, Chang Xu, Bo Du, Honglak Lee
ICCV 2021 Pathdreamer: A World Model for Indoor Navigation Jing Yu Koh, Honglak Lee, Yinfei Yang, Jason Baldridge, Peter Anderson
IJCAI 2021 Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in a First-Person Simulated 3D Environment Wilka Carvalho, Anthony Liang, Kimin Lee, Sungryull Sohn, Honglak Lee, Richard L. Lewis, Satinder Singh
ICLR 2021 Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction Wonkwang Lee, Whie Jung, Han Zhang, Ting Chen, Jing Yu Koh, Thomas Huang, Hyungsuk Yoon, Honglak Lee, Seunghoon Hong
NeurIPSW 2021 SURF: Semi-Supervised Reward Learning with Data Augmentation for Feedback-Efficient Preference-Based Reinforcement Learning Jongjin Park, Younggyo Seo, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
ICML 2021 Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm H Van Seijen, Mehdi Fatemi, Honglak Lee
ICML 2021 State Entropy Maximization with Random Encoders for Efficient Exploration Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
NeurIPS 2021 Successor Feature Landmarks for Long-Horizon Goal-Conditioned Reinforcement Learning Christopher Hoang, Sungryull Sohn, Jongwook Choi, Wilka Carvalho, Honglak Lee
WACV 2021 Text-to-Image Generation Grounded by Fine-Grained User Attention Jing Yu Koh, Jason Baldridge, Honglak Lee, Yinfei Yang
ICML 2021 Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Shane Gu
NeurIPS 2021 Why Do Better Loss Functions Lead to Less Transferable Features? Simon Kornblith, Ting Chen, Honglak Lee, Mohammad Norouzi
IJCAI 2020 BRPO: Batch Residual Policy Optimization Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi, Craig Boutilier
NeurIPS 2020 Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning Guangxiang Zhu, Minghao Zhang, Honglak Lee, Chongjie Zhang
WACV 2020 CompressNet: Generative Compression at Extremely Low Bitrates Suraj Kiran Raman, Aditya Ramesh, Vijayakrishna Naganoor, Shubham Dash, Giridharan Kumaravelu, Honglak Lee
ICLR 2020 Consistency Regularization for Generative Adversarial Networks Han Zhang, Zizhao Zhang, Augustus Odena, Honglak Lee
ICML 2020 Context-Aware Dynamics Model for Generalization in Model-Based Reinforcement Learning Kimin Lee, Younggyo Seo, Seunghyun Lee, Honglak Lee, Jinwoo Shin
ECCV 2020 High-Fidelity Synthesis with Disentangled Representation Wonkwang Lee, Donggyun Kim, Seunghoon Hong, Honglak Lee
AAAI 2020 How Should an Agent Practice? Janarthanan Rajendran, Richard L. Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh
NeurIPS 2020 Memory Based Trajectory-Conditioned Policies for Learning from Sparse Rewards Yijie Guo, Jongwook Choi, Marcin Moczulski, Shengyu Feng, Samy Bengio, Mohammad Norouzi, Honglak Lee
ICLR 2020 Meta Reinforcement Learning with Autonomous Inference of Subtask Dependencies Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Honglak Lee
ICLR 2020 Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning Kimin Lee, Kibok Lee, Jinwoo Shin, Honglak Lee
NeurIPS 2020 Ode to an ODE Krzysztof M Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani
NeurIPS 2020 Predictive Information Accelerates Learning in RL Kuang-Huei Lee, Ian Fischer, Anthony Liu, Yijie Guo, Honglak Lee, John Canny, Sergio Guadarrama
ECCV 2020 SemanticAdv: Generating Adversarial Examples via Attribute-Conditioned Image Editing Haonan Qiu, Chaowei Xiao, Lei Yang, Xinchen Yan, Honglak Lee, Bo Li
ICLRW 2020 Time Dependence in Non-Autonomous Neural ODEs Jared Quincy Davis, Krzysztof Choromanski, Vikas Sindhwani, Jake Varley, Honglak Lee, Jean-Jacques Slotine, Valerii Likhosterov, Adrian Weller, Ameesh Makadia
ICLR 2019 Contingency-Aware Exploration in Reinforcement Learning Jongwook Choi, Yijie Guo, Marcin Moczulski, Junhyuk Oh, Neal Wu, Mohammad Norouzi, Honglak Lee
ICLR 2019 Diversity-Sensitive Conditional Generative Adversarial Networks Dingdong Yang, Seunghoon Hong, Yunseok Jang, Tianchen Zhao, Honglak Lee
NeurIPS 2019 High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V Le, Honglak Lee
CVPRW 2019 Incremental Learning with Unlabeled Data in the Wild Kibok Lee, Kimin Lee, Jinwoo Shin, Honglak Lee
ICML 2019 Learning Latent Dynamics for Planning from Pixels Danijar Hafner, Timothy Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, James Davidson
ICLR 2019 Near-Optimal Representation Learning for Hierarchical Reinforcement Learning Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
ICML 2019 Robust Inference via Generative Classifiers for Handling Noisy Labels Kimin Lee, Sukmin Yun, Kibok Lee, Honglak Lee, Bo Li, Jinwoo Shin
ICML 2019 Similarity of Neural Network Representations Revisited Simon Kornblith, Mohammad Norouzi, Honglak Lee, Geoffrey Hinton
NeurIPS 2019 Unsupervised Learning of Object Structure and Dynamics from Videos Matthias Minderer, Chen Sun, Ruben Villegas, Forrester Cole, Kevin P. Murphy, Honglak Lee
NeurIPS 2018 A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee, Kibok Lee, Honglak Lee, Jinwoo Shin
AAAI 2018 Addressee and Response Selection in Multi-Party Conversations with Speaker Interaction RNNs Rui Zhang, Honglak Lee, Lazaros Polymenakos, Dragomir R. Radev
ICLR 2018 An Efficient Framework for Learning Sentence Representations Lajanugen Logeswaran, Honglak Lee
NeurIPS 2018 Content Preserving Text Generation with Attribute Controls Lajanugen Logeswaran, Honglak Lee, Samy Bengio
NeurIPS 2018 Data-Efficient Hierarchical Reinforcement Learning Ofir Nachum, Shixiang Gu, Honglak Lee, Sergey Levine
ICML 2018 Hierarchical Long-Term Video Prediction Without Supervision Nevan Wichers, Ruben Villegas, Dumitru Erhan, Honglak Lee
NeurIPS 2018 Hierarchical Reinforcement Learning for Zero-Shot Generalization with Subtask Dependencies Sungryull Sohn, Junhyuk Oh, Honglak Lee
NeurIPS 2018 Learning Hierarchical Semantic Image Manipulation Through Structured Representations Seunghoon Hong, Xinchen Yan, Thomas S. Huang, Honglak Lee
ECCV 2018 MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics Xinchen Yan, Akash Rastogi, Ruben Villegas, Kalyan Sunkavalli, Eli Shechtman, Sunil Hadap, Ersin Yumer, Honglak Lee
NeurIPS 2018 Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion Jacob Buckman, Danijar Hafner, George Tucker, Eugene Brevdo, Honglak Lee
ICML 2018 Self-Imitation Learning Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee
AAAI 2018 Sentence Ordering and Coherence Modeling Using Recurrent Neural Networks Lajanugen Logeswaran, Honglak Lee, Dragomir R. Radev
ICLR 2018 Training Confidence-Calibrated Classifiers for Detecting Out-of-Distribution Samples Kimin Lee, Honglak Lee, Kibok Lee, Jinwoo Shin
ICLR 2017 Decomposing Motion and Content for Natural Video Sequence Prediction Ruben Villegas, Jimei Yang, Seunghoon Hong, Xunyu Lin, Honglak Lee
CVPR 2017 Discriminative Bimodal Networks for Visual Localization and Detection with Natural Language Queries Yuting Zhang, Luyao Yuan, Yijie Guo, Zhiyuan He, I-An Huang, Honglak Lee
ICML 2017 Learning to Generate Long-Term Future via Hierarchical Prediction Ruben Villegas, Jimei Yang, Yuliang Zou, Sungryull Sohn, Xunyu Lin, Honglak Lee
IJCAI 2017 Towards Understanding the Invertibility of Convolutional Neural Networks Anna C. Gilbert, Yi Zhang, Kibok Lee, Yuting Zhang, Honglak Lee
NeurIPS 2017 Value Prediction Network Junhyuk Oh, Satinder Singh, Honglak Lee
CVPR 2017 Weakly Supervised Semantic Segmentation Using Web-Crawled Videos Seunghoon Hong, Donghun Yeo, Suha Kwak, Honglak Lee, Bohyung Han
ICML 2017 Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kohli
ECCV 2016 Attribute2Image: Conditional Image Generation from Visual Attributes Xinchen Yan, Jimei Yang, Kihyuk Sohn, Honglak Lee
ICML 2016 Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-Scale Image Classification Yuting Zhang, Kibok Lee, Honglak Lee
ICML 2016 Control of Memory, Active Perception, and Action in Minecraft Junhyuk Oh, Valliappa Chockalingam, Satinder, Honglak Lee
IJCAI 2016 Deep Learning for Reward Design to Improve Monte Carlo Tree Search in ATARI Games Xiaoxiao Guo, Satinder Singh, Richard L. Lewis, Honglak Lee
ICML 2016 Generative Adversarial Text to Image Synthesis Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, Honglak Lee
CVPR 2016 Learning Deep Representations of Fine-Grained Visual Descriptions Scott Reed, Zeynep Akata, Honglak Lee, Bernt Schiele
CVPR 2016 Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network Seunghoon Hong, Junhyuk Oh, Honglak Lee, Bohyung Han
NeurIPS 2016 Learning What and Where to Draw Scott E Reed, Zeynep Akata, Santosh Mohan, Samuel Tenka, Bernt Schiele, Honglak Lee
CVPR 2016 Object Contour Detection with a Fully Convolutional Encoder-Decoder Network Jimei Yang, Brian Price, Scott Cohen, Honglak Lee, Ming-Hsuan Yang
NeurIPS 2016 Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction Without 3D Supervision Xinchen Yan, Jimei Yang, Ersin Yumer, Yijie Guo, Honglak Lee
ICML 2016 Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units Wenling Shang, Kihyuk Sohn, Diogo Almeida, Honglak Lee
NeurIPS 2015 Action-Conditional Video Prediction Using Deep Networks in Atari Games Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard L. Lewis, Satinder Singh
NeurIPS 2015 Deep Visual Analogy-Making Scott E Reed, Yi Zhang, Yuting Zhang, Honglak Lee
CVPR 2015 Evaluation of Output Embeddings for Fine-Grained Image Classification Zeynep Akata, Scott Reed, Daniel Walter, Honglak Lee, Bernt Schiele
CVPR 2015 Improving Object Detection with Deep Convolutional Networks via Bayesian Optimization and Structured Prediction Yuting Zhang, Kihyuk Sohn, Ruben Villegas, Gang Pan, Honglak Lee
NeurIPS 2015 Learning Structured Output Representation Using Deep Conditional Generative Models Kihyuk Sohn, Honglak Lee, Xinchen Yan
ICLR 2015 Training Deep Neural Networks on Noisy Labels with Bootstrapping Scott E. Reed, Honglak Lee, Dragomir Anguelov, Christian Szegedy, Dumitru Erhan, Andrew Rabinovich
NeurIPS 2015 Weakly-Supervised Disentangling with Recurrent Transformations for 3D View Synthesis Jimei Yang, Scott E Reed, Ming-Hsuan Yang, Honglak Lee
NeurIPS 2014 Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning Xiaoxiao Guo, Satinder Singh, Honglak Lee, Richard L. Lewis, Xiaoshi Wang
NeurIPS 2014 Improved Multimodal Deep Learning with Variation of Information Kihyuk Sohn, Wenling Shang, Honglak Lee
ICML 2014 Learning to Disentangle Factors of Variation with Manifold Interaction Scott Reed, Kihyuk Sohn, Yuting Zhang, Honglak Lee
ICML 2014 Structured Recurrent Temporal Restricted Boltzmann Machines Roni Mittelman, Benjamin Kuipers, Silvio Savarese, Honglak Lee
NeurIPS 2013 Adaptive Multi-Column Deep Neural Networks with Application to Robust Image Denoising Forest Agostinelli, Michael R Anderson, Honglak Lee
CVPR 2013 Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling Andrew Kae, Kihyuk Sohn, Honglak Lee, Erik Learned-Miller
ICLR 2013 Deep Learning for Detecting Robotic Grasps Ian Lenz, Honglak Lee, Ashutosh Saxena
ICML 2013 Learning and Selecting Features Jointly with Point-Wise Gated Boltzmann Machines Kihyuk Sohn, Guanyu Zhou, Chansoo Lee, Honglak Lee
CVPR 2013 Weakly Supervised Learning of Mid-Level Features with Beta-Bernoulli Process Restricted Boltzmann Machines Roni Mittelman, Honglak Lee, Benjamin Kuipers, Silvio Savarese
CVPR 2012 An Efficient Branch-and-Bound Algorithm for Optimal Human Pose Estimation Min Sun, Murali Telaprolu, Honglak Lee, Silvio Savarese
AISTATS 2012 Efficient Distributed Linear Classification Algorithms via the Alternating Direction Method of Multipliers Caoxie Zhang, Honglak Lee, Kang Shin
AISTATS 2012 Efficient and Exact MAP-MRF Inference Using Branch and Bound Min Sun, Murali Telaprolu, Honglak Lee, Silvio Savarese
CVPR 2012 Learning Hierarchical Representations for Face Verification with Convolutional Deep Belief Networks Gary B. Huang, Honglak Lee, Erik G. Learned-Miller
ICML 2012 Learning Invariant Representations with Local Transformations Kihyuk Sohn, Honglak Lee
NeurIPS 2012 Learning to Align from Scratch Gary Huang, Marwan Mattar, Honglak Lee, Erik G. Learned-miller
AISTATS 2012 Online Incremental Feature Learning with Denoising Autoencoders Guanyu Zhou, Kihyuk Sohn, Honglak Lee
AISTATS 2011 An Analysis of Single-Layer Networks in Unsupervised Feature Learning Adam Coates, Andrew Ng, Honglak Lee
ICCV 2011 Efficient Learning of Sparse, Distributed, Convolutional Feature Representations for Object Recognition Kihyuk Sohn, Dae Yon Jung, Honglak Lee, Alfred O. Hero Iii
ICML 2011 Multimodal Deep Learning Jiquan Ngiam, Aditya Khosla, Mingyu Kim, Juhan Nam, Honglak Lee, Andrew Y. Ng
ICML 2009 Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations Honglak Lee, Roger B. Grosse, Rajesh Ranganath, Andrew Y. Ng
IJCAI 2009 Exponential Family Sparse Coding with Application to Self-Taught Learning Honglak Lee, Rajat Raina, Alex Teichman, Andrew Y. Ng
NeurIPS 2009 Measuring Invariances in Deep Networks Ian Goodfellow, Honglak Lee, Quoc V. Le, Andrew Saxe, Andrew Y. Ng
NeurIPS 2009 Unsupervised Feature Learning for Audio Classification Using Convolutional Deep Belief Networks Honglak Lee, Peter Pham, Yan Largman, Andrew Y. Ng
ICML 2007 Self-Taught Learning: Transfer Learning from Unlabeled Data Rajat Raina, Alexis J. Battle, Honglak Lee, Benjamin Packer, Andrew Y. Ng
NeurIPS 2007 Sparse Deep Belief Net Model for Visual Area V2 Honglak Lee, Chaitanya Ekanadham, Andrew Y. Ng
CVPR 2006 A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image Erick Delage, Honglak Lee, Andrew Y. Ng
AAAI 2006 Efficient L1 Regularized Logistic Regression Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. Ng
NeurIPS 2006 Efficient Sparse Coding Algorithms Honglak Lee, Alexis Battle, Rajat Raina, Andrew Y. Ng