Published in International Conference on Learning Representations, 2021
We construct and analyze new datasets for evaluating disentanglement on natural videos. We also propose a temporally sparse prior for identifying the underlying factors of variation in natural videos.
Published in Journal of Vision, 2020
Using differential geometry we explain how sparse coding networks bend their response surfaces, which results in improved selectivity and robustness for individual neurons.
Published in Neuro-Inspired Computational Elements, 2020
We present a 2-layer recurrent sparse coding network for learning higher order statistical regularities in natural images.
Published in UC Berkeley Thesis, 2019
My PhD thesis provides an in-depth account of a recurrent network for sparse inference, including novel analyses, comparisons, and extensions.
Published in IEEE International Electron Devices Meeting (IEDM), 2018
The first published approach for storing digital natural images onto resistive random access memory arrays.
Published in Neural Information Processing Systems, 2018
A hierarchical sparse coding model that decomposes scenes into constituent parts and linearizes temporal trajectories of natural videos.
Published in Data Compression Conference, 2018
A convolutional autoencoder with divisive normalization enables digital image storage on simulated emerging memristive devices.
Published in Proceedings of the 9th EAI International Conference on Bio-inspired Information and Communications Technologies, 2016
A hierarchical sparse coding network that learns bandpass decompositions of natural images.
Published in IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI), 2016
A convolutional sparse coding network facilitates better depth inference than comparable feedforward networks.
Published in arXiv Preprint, 2014
Exploring the tradeoff of patch size, stride, and overcompleteness in convolutional sparse coding.
Published in The International Joint Conference on Neural Networks (IJCNN), 2013
Computer simulations of distributed sensor networks using a retina-inspired communication protocol to amplify signals.
Published in IEEE Southwest Symposium on Image Analysis and Interpretation, 2012
Labeling videos with objects using independent color/texture and shape/form processing streams.
You can also find my articles on my Google Scholar profile.