@AmyZhaoMIT

Computer vision and machine learning researcher working on @Oculus at Facebook Reality Labs. PhD from @MIT_CSAIL.

 Redmond, WA
people.csail.mit.edu/xamyzhao
Joined December 2018
  • Tweets23
  • Following48
  • Followers143
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We're releasing a restructured #VoxelMorph registration (and much more) library at voxelmorph.net! Available in @pypi, support for both #tensorflow/#keras and #pytorch! Just in time for @MICCAI2020 :). @MIT_CSAIL @MIT @MGHMartinos @LCN @mit_caml github.com/voxelmorph/voxelm…
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Tun in Thursday (July 23) @CHILconference -- @KatieLewisMIT will be presenting her work on registering clinical quality images (presentation video prerecorded - watch now! Q&A at 1:25 PM EST). with @nsanar and John Guttag @MIT_CSAIL @mit_caml ! Info: chilconference.org/poster_33…
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Thanks @VentureBeat for the feature! "MIT researchers train AI to predict how humans paint works of art: venturebeat.com/2020/06/17/m…" We are doing a live Q&A now for #CVPR2020 attendees! :) cvpr20.com/event/painting-ma…
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Excited for tomorrow's Q&A about my final research project from my PhD at MIT: synthesizing time lapses of paintings! #CVPR2020
Adrian Dalca@AdrianDalca16 Jun 2020
Replying to @AmyZhaoMIT
@AmyZhaoMIT will be presenting her awesome work on Synthesizing Paintings of Time Lapse Videos on Wed 2-4pm PST. #cvpr2020 Q&A: cvpr20.com/event/painting-ma… Project: xamyzhao.github.io/timecraft… with @balaguha, @KatieLewisMIT, @fredodurand, John Guttag, @mit_caml @MIT_CSAIL
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Amy Zhao retweeted
AK
@_akhaliq7 Jan 2020
Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings pdf: arxiv.org/pdf/2001.01026.pdf abs: arxiv.org/abs/2001.01026 project page: xamyzhao.github.io/timecraft… video: youtu.be/iy1FCPQs4JI
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Our work on synthesizing time lapses of paintings is now up on arXiv! What a fun and challenging project with @balaguha @KatieLewisMIT @AdrianDalca xamyzhao.github.io/timecraft

Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings

A learning-based method for synthesizing time lapse videos of paintings

xamyzhao.github.io
DeepAI
@DeepAI7 Jan 2020
Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings deepai.org/publication/paint… by Amy Zhao et al. including @AdrianDalca #ConvolutionalNeuralNetworks #NeuralNetwork

Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings

01/04/20 - We introduce a new video synthesis task: synthesizing time lapse videos depicting how a given painting might have been created. Ar...

deepai.org
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Thank you @RSIPvision for the interview and the feature!
MIT Clinical and Applied Machine Learning@mit_caml1 Jul 2019
Amy continues to dominate the data augmentation game with a "Best of CVPR 2019" feature by @RSIPvision - congratulations to @AmyZhaoMIT! rsipvision.com/ComputerVisio…

Computer Vision News - July 2019

The magazine of the algorithm community

rsipvision.com
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Talking about learned data augmentation with co-authors Guha Balakrishnan and @AdrianDalca at poster 192 today! #CVPR2019 #MRI
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Also check out @AmyZhaoMIT's feature in #CVPR2019 daily at rsipvision.com/CVPR2019-Thur… @RSIPvision @mit_caml

CVPR Daily - 2019 Thursday

CVPR Daily - 2019 Thursday

rsipvision.com
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"One scan, no problem." A great article and interview by MIT news about our #CVPR2019 paper on data augmentation and one-shot #MRI segmentation! We talk about the method, its applications, and its fun roots in #MagicTheGathering.
MIT Siegel Family Quest for Intelligence (SQI)@MIT_Quest19 Jun 2019
“We’re hoping this will make image segmentation more accessible in realistic situations where you don’t have a lot of training data.” Don't miss @AmyZhaoMIT tomorrow at #CVPR2019. bit.ly/2XY6qCF

From one brain scan, more information for medical artificial intelligence

MIT researchers have devised a novel method to glean training information for machine-learning models, including those that can analyze medical images to help diagnose and treat brain conditions.

news.mit.edu
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Talking about Magic: The Gathering today, brain MRIs on Thursday! Data augmentation is useful everywhere :)
MIT Clinical and Applied Machine Learning@mit_caml16 Jun 2019
Check out @AmyZhaoMIT’s work at poster 160 during the #wicv workshop at #CVPR2019. She shows that by learning transformations to synthesize labeled data, you can improve few shot classification accuracy. She’ll also be talking about it during an oral on Thursday morning 💪🏾
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Replying to @KatieLewisMIT
@KatieLewisMIT is presenting her work at poster 147 during the #wicv workshop at #CVPR2019! Stop by to learn more about her method for faster, more accurate registration for MRI images 🧠
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Our paper on learning how to do data augmentation (accepted to #cvpr2019) is up on arXiv! We show how to use our method to do medical image segmentation with just a single labeled example. We use publicly available datasets and our code is up on #github :) github.com/xamyzhao/brainsto…

GitHub - xamyzhao/brainstorm: Implementation of "Data augmentation using learned transforms for...

Implementation of "Data augmentation using learned transforms for one-shot medical image segmentation" - xamyzhao/brainstorm

github.com
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Encore presentation @ #ML4H by @KatieLewisMIT on SparseVM, a fast learning-based approach to clinical image presentation! Learn more at the poster session at 11:30, room 517D 🤓
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Katie Lewis fielding questions on “SparseVM: Learning-based Registration of Sparse Clinical Images” before the WiML evening poster session!
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Lab alum @Jen_Gong presenting at WiML on her recent work, “Discovering heterogeneous subpopulations for fine-grained analysis of opioid use and opioid use disorders”!
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