Publications

Journal Articles

• Accuracy Maximization Analysis for Natural Tasks and Principles of Multiplicative Noise and Filter Correlation in Neural Coding
  Johannes Burge and Priyank Jaini
  Public Library of Science - Computational Biology (PLoS), 2017
  [pdf] [code]

• Accuracy Maximization Analysis with Class-conditional Gaussians : Linking Normative and Descriptive Quadratic Models of Neural Response
  Priyank Jaini and Johannes Burge
  Journal of Vision (JoV), 2017
  [pdf] [code]

Conference & Workshop Papers (Refereed and Archived)

• Deep Homogeneous Mixture Models : Representation, Separation, and Approximation
  Priyank Jaini, Pascal Poupart, and Yaoliang Yu
  Neural Information Processing Systems (NeurIPS), 2018
  

• Prometheus: Directly Learning Acyclic Directed Graph Structures for Sum-Product Networks
  Priyank Jaini, Amur Ghosh and, Pascal Poupart
  9th International Conference on Probabilistic Graphical Models (PGM), 2018
  

• Depth Efficiency of Deep Mixture Models and Sum-Product Networks using Tensor Analysis
  Priyank Jaini, Pascal Poupart and, Yaoliang Yu
  Workshop on Deep Learning Theory, International Conference of Machine Learning (ICML), 2018
  

• Linking Normative Models and Methods for Neural Systems Identification
  Priyank Jaini and Johannes Burge
  Computational and Systems Neuroscience (COSYNE), 2017
  

• Online Bayesian Transfer Learning for Sequential Data Modeling
  Priyank Jaini, Zhitang Chen, Pablo Carbajal, Edith Law, Laura Middleton, Kayla Regan, Mike Schaekermann, George Trimponias, James Tung, Pascal Poupart
  In the Proceedings of the 5th International Conference on Learning Representations (ICLR 2017)
  [pdf] [poster]

• Online Algorithms for Sum-Product Networks with Continuous Variables
  Priyank Jaini, Abdullah Rashwan, Han Zhao, Yue Liu, Ershad Banijamali, Chen Zhitang and Pascal Poupart
  In the Proceedings of the 8th International Conference on Probabilistic Graphical Models (2016)
  [pdf] [code]

• Online and Distributed Learning of Gaussian Mixture Models by Bayesian Moment Matching
  Priyank Jaini and Pascal Poupart
  Workshop on Approximate Bayesian Inference Inference, Neural Information and Processing Systems (NIPS), 2017
  [pdf] [arxiv link]

• Online Flow Size Prediction for Improved Network Routing
  Pascal Poupart, Zhitang Chen, Priyank Jaini, Yanhui Geng, Li Chen, Kai Chen and Hao Jin
  IEEE ICNP Workshop on Machine Learning in Computer Networks (NetworkML 2016)
  [pdf]

Thesis

• Lasso, Lasso* and Lad-Lasso for Sinusoidal Time Series Model
  Indian Institute of Technology - Kanpur (2015)