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Generative Neurosymbolic Machines


Oct 23, 2020
Jindong Jiang, Sungjin Ahn

* Accepted in NeurIPS as spotlight 

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Improving Generative Imagination in Object-Centric World Models


Oct 05, 2020
Zhixuan Lin, Yi-Fu Wu, Skand Peri, Bofeng Fu, Jindong Jiang, Sungjin Ahn

* Accepted in ICML 2020 

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Robustifying Sequential Neural Processes


Jun 29, 2020
Jaesik Yoon, Gautam Singh, Sungjin Ahn

* Accepted in ICML 2020 

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Learning to Infer 3D Object Models from Images


Jun 11, 2020
Chang Chen, Fei Deng, Sungjin Ahn

* First two authors contributed equally 

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SPACE: Unsupervised Object-Oriented Scene Representation via Spatial Attention and Decomposition


Feb 18, 2020
Zhixuan Lin, Yi-Fu Wu, Skand Vishwanath Peri, Weihao Sun, Gautam Singh, Fei Deng, Jindong Jiang, Sungjin Ahn

* Accepted in ICLR 2020 

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Neural Multisensory Scene Inference


Nov 08, 2019
Jae Hyun Lim, Pedro O. Pinheiro, Negar Rostamzadeh, Christopher Pal, Sungjin Ahn


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Generative Hierarchical Models for Parts, Objects, and Scenes


Oct 21, 2019
Fei Deng, Zhuo Zhi, Sungjin Ahn


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Scalable Object-Oriented Sequential Generative Models


Oct 06, 2019
Jindong Jiang, Sepehr Janghorbani, Gerard de Melo, Sungjin Ahn

* First two authors contributed equally. 20 pages with appendix including implementation details 

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Variational Temporal Abstraction


Oct 02, 2019
Taesup Kim, Sungjin Ahn, Yoshua Bengio

* Accepted in NeurIPS 2019 

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Sequential Neural Processes


Jul 14, 2019
Gautam Singh, Jaesik Yoon, Youngsung Son, Sungjin Ahn

* First two authors contributed equally. 27 pages with appendix including experimental details 

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Reinforced Imitation in Heterogeneous Action Space


Apr 06, 2019
Konrad Zolna, Negar Rostamzadeh, Yoshua Bengio, Sungjin Ahn, Pedro O. Pinheiro

* The extended version of the work "Reinforced Imitation Learning from Observations" presented on the NeurIPS workshop "Imitation Learning and its Challenges in Robotics" 

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Learning Single-View 3D Reconstruction with Adversarial Training


Dec 04, 2018
Pedro O. Pinheiro, Negar Rostamzadeh, Sungjin Ahn


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Bayesian Model-Agnostic Meta-Learning


Oct 29, 2018
Taesup Kim, Jaesik Yoon, Ousmane Dia, Sungwoong Kim, Yoshua Bengio, Sungjin Ahn

* First two authors contributed equally. 15 pages with appendix including experimental details. Accepted in NIPS 2018 

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Hierarchical Multiscale Recurrent Neural Networks


Mar 09, 2017
Junyoung Chung, Sungjin Ahn, Yoshua Bengio


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A Neural Knowledge Language Model


Mar 02, 2017
Sungjin Ahn, Heeyoul Choi, Tanel Pärnamaa, Yoshua Bengio


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Pointing the Unknown Words


Aug 21, 2016
Caglar Gulcehre, Sungjin Ahn, Ramesh Nallapati, Bowen Zhou, Yoshua Bengio

* ACL 2016 Oral Paper 

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Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus


May 29, 2016
Iulian Vlad Serban, Alberto García-Durán, Caglar Gulcehre, Sungjin Ahn, Sarath Chandar, Aaron Courville, Yoshua Bengio

* 13 pages, 1 figure, 7 tables 

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Hierarchical Memory Networks


May 24, 2016
Sarath Chandar, Sungjin Ahn, Hugo Larochelle, Pascal Vincent, Gerald Tesauro, Yoshua Bengio

* 10 pages 

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Denoising Criterion for Variational Auto-Encoding Framework


Jan 04, 2016
Daniel Jiwoong Im, Sungjin Ahn, Roland Memisevic, Yoshua Bengio

* ICLR conference submission 

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Scalable MCMC for Mixed Membership Stochastic Blockmodels


Oct 22, 2015
Wenzhe Li, Sungjin Ahn, Max Welling

* 9 pages, 18 figures 

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Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC


Mar 10, 2015
Sungjin Ahn, Anoop Korattikara, Nathan Liu, Suju Rajan, Max Welling


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Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring


Jun 27, 2012
Sungjin Ahn, Anoop Korattikara, Max Welling

* Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012) 

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