Rutgers Machine Learning Group


  • Learning Single-View 3D Reconstruction with Adversarial Training [pdf]
    P. Pinheiro, N. Rostamzadeh, S. Ahn
    International Conference on Computer Vision (ICCV) Oral (4.3% of all the submitted)

  • Sequential Neural Processes [pdf] [project]
    G. Singh*, J. Yoon*, Y. Sohn, S. Ahn (* indicates equal contribution)

  • Variational Temporal Abstraction [pdf]
    T. Kim, S. Ahn*, Y. Bengio* (* indicates equal advising)
    ICML Workshop on Generative Modeling and Model-Based Reasoning for Robotics and AI 

  • Reinforced Imitation in Heterogeneous Action Space [pdf]
    Konrad Zolna, Negar Rostamzadeh, Yoshua Bengio, Sungjin Ahn, Pedro O. Pinheiro
  • Reinforced Imitation Learning from Observations [pdf]
    K. Żołna, N. Rostamzadeh, Y. Bengio, S. Ahn+, P. Pinheiro+  (+ indicates equal advising)
    NeurIPS 18 Workshop on Imitation Learning and Its Challenges in Robotics

  • Bayesian Model-Agnostic Meta-Learning [pdf
    T Kim*, J Yoon*, O. Dia, S. Kim, Y. BengioS. Ahn  [* indicates equal contribution]
    Neural Information Processing Systems Spotlight (top 3.5% = 168/4856)
  • Hierarchical Multiscale Recurrent Neural Networks [pdf]
    J. Chung, S. AhnY. Bengio
    International Conference on Learning Representations

  • Denoising Criterion for Variational Auto-Encoding Framework 
    D. Im, S. Ahn, R. Memisevic, Y. Bengio
    AAAI-17 [pdf]

  • SENA: Preserving Social Structure for Network Embedding 
  • S. Hong, T. Chakraborty, S. Ahn, G. Husari and N. Park 
    ACM Conference on Hypertext and Social Media
  • A Neural Knowledge Language Model
    S. Ahn, H. Choi, T. Parnamaa, Y. Bengio
    [ArXiv16] [pdf] [dataset]

  • Hierarchical Memory Networks
    S. Chandar, S. Ahn, H. Larochelle, P. Vincent, G. Tasauro, Y. Bengio
    [ArXiv16] [pdf]

  • Learning Latent Multiscale Structure using Recurrent Neural Networks
    J. Chung, S. AhnY. Bengio
    NIPS 2016 Workshop on Neural Abstract Machines & Program Induction (NAMPI)

  • Pointing the Unknown Words 
    C. Gulcehre, S. Ahn, R. Nallapati, B. Zhou, Y. Bengio.
    [ACL16] [pdf]

  • Generating Factoid Questions with Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus
    I. V. Serban*, A. G. Duran*, C. Gulcehre, S. Ahn, S. Chandar, A. Courville, Y. Bengio 
    (* Equal contribution)
    [ACL16] [pdf] [dataset

  • Scalable MCMC for Mixed Membership Stochastic Blockmodels 
    W. Li*S. Ahn*, and M. Welling (* Equal contribution)
    [AISTATS16] [pdf

  • Scalable Overlapping Community Detection
    I. El-Helw, R. Hofman, W. Li, S. Ahn, M. Welling, H. Bal
  • [ParLearning16] [pdfBest Paper Award
~2015 (selected publications)
  • Stochastic Gradient MCMC: Algorithms and Applications 
    [PhD Dissertation 15] [pdf]

  • Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC
    S. Ahn, A. Korattikara, N. Liu, S. Rajan, and M. Welling
    [KDD15] [pdf] (Acceptance Rate: 19%)

  • Distributed Stochastic Gradient MCMC
    S. Ahn, B. Shahbaba, and M. Welling
    [ICML14] [pdf

  • Distributed and Adaptive Darting Monte Carlo through Regenerations
    S. Ahn, Y. Chen, and M. Welling
    [AISTATS13] [pdf

  • Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring
    S. Ahn, A. Korattikara, and M. Welling
    [ICML12] [pdfBest Paper Award