NIPS Proceedingsβ

Richard Zemel

7 Papers

  • Learning Deep Parsimonious Representations (2016)
  • Understanding the Effective Receptive Field in Deep Convolutional Neural Networks (2016)
  • Exploring Models and Data for Image Question Answering (2015)
  • Skip-Thought Vectors (2015)
  • A Multiplicative Model for Learning Distributed Text-Based Attribute Representations (2014)
  • A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data (2013)
  • On the Representational Efficiency of Restricted Boltzmann Machines (2013)