Page Not Found
Page not found. Your pixels are in another canvas.
Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About Me
Gauri Jagatap is a Senior Researcher at Dolby Laboratories working on multimodal AI for long-form video understanding.
Page not in menu
This is a page not in th emain menu
Posts
Future Blog Post
Published:
This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.
Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
portfolio
Multimodal Understanding of Long-Form Video
Models that combine video, audio and text to retrieve moments, answer questions, localize actions and curate highlights in long videos.
Other Dolby Projects
HDR for Dolby Vision 2, and real-time active speaker detection for mobile devices and smart glasses.
Inverse Imaging with Deep Untrained Neural Network Priors
Untrained deep networks as image priors for compressed sensing, phase retrieval and HDR imaging, with convergence guarantees.
Adversarially Robust Learning via Entropic Regularization
ATENT: an entropy-regularized loss for training neural networks that are robust to adversarial perturbations.
Provable algorithms for machine learning
Gradient descent and alternating minimization for shallow ResNets, with linear convergence guarantees.
Compressive phase retrieval under image priors
CoPRAM and Block CoPRAM: fast, sample-efficient phase retrieval using sparsity and structured sparsity.
Fourier ptychography for super-resolution under image priors
Sub-diffraction imaging via Fourier ptychography using sparsity and low-rank priors.
Older Projects
Course and side projects from graduate school: CGI image forensics, topic modeling with NMF and sparse PCA, and compressive video segmentation.
publications
Fast, sample efficient algorithms for structured phase retrieval
Published in Advances in Neural Information Processing Systems (NIPS), 2017
Compressive phase retrieval using signal priors.
Low-rank Fourier ptychography
Published in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018
Using low-rank priors for efficient ptychography based video super-resolution.
Sub-diffraction imaging using Fourier ptychography and structured sparsity
Published in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018
Using sparsity priors for efficient ptychography based image super-resolution.
Towards Sample-Optimal Methods for Solving Random Quadratic Equations with Structure
Published in IEEE International Symposium on Information Theory (ISIT), 2018
Using signal priors for efficient compressive phase retrieval.
Sample efficient algorithms for recovering structured signals from magnitude-only measurements
Published in IEEE Transactions on Information Theory, 2019
Compressive phase retrieval using signal priors under noisy Gaussian measurements.
Linearly Convergent Algorithms for Learning Shallow Residual Networks
Published in IEEE International Symposium on Information Theory (ISIT), 2019
Linear convergence analysis for learning shallow networks with alternating minimization and gradient descent.
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.