NIPS Proceedingsβ

Ryan P. Adams

18 Papers

  • Bayesian latent structure discovery from multi-neuron recordings (2016)
  • Composing graphical models with neural networks for structured representations and fast inference (2016)
  • A Gaussian Process Model of Quasar Spectral Energy Distributions (2015)
  • Convolutional Networks on Graphs for Learning Molecular Fingerprints (2015)
  • Dependent Multinomial Models Made Easy: Stick-Breaking with the Polya-gamma Augmentation (2015)
  • Spectral Representations for Convolutional Neural Networks (2015)
  • A framework for studying synaptic plasticity with neural spike train data (2014)
  • A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data (2013)
  • Contrastive Learning Using Spectral Methods (2013)
  • Message Passing Inference with Chemical Reaction Networks (2013)
  • Multi-Task Bayesian Optimization (2013)
  • Cardinality Restricted Boltzmann Machines (2012)
  • Practical Bayesian Optimization of Machine Learning Algorithms (2012)
  • Priors for Diversity in Generative Latent Variable Models (2012)
  • Probabilistic n-Choose-k Models for Classification and Ranking (2012)
  • Slice sampling covariance hyperparameters of latent Gaussian models (2010)
  • Tree-Structured Stick Breaking for Hierarchical Data (2010)
  • The Gaussian Process Density Sampler (2008)