Priyank Jaini bio photo

Priyank Jaini

Fourth Year Ph.D. Student
Artificial Intelligence Lab
University of Waterloo

Email

Publications

Overview


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)

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