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    Publications: Cell Assemblies in PNAS

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    Research: Learning Visual Representation

  • IQ Engines

    IQ Engines, putting visual search in your pocket

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Wired: Machines Finally Match Monkeys in Key Image-Recognition Test

Wired: Machines Finally Match Monkeys in Key Image-Recognition Test

Jul 20, 2014

Wired ran a piece on our work at the DiCarlo Lab comparing deep neural networks and monkey IT.  This was a real group effort!  You can find the piece here: Machines Finally Match Monkeys in Key Image-Recognition Test  

arXiv: Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition

arXiv: Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition

Jun 13, 2014

We have posted to arXiv the latest results in our comparisons between deep neural networks and monkey high level visual cortex (IT).  The paper presents an improved methodology over the results from ICLR 2013.  Find it here: Charles F. Cadieu, Ha Hong, Daniel L. K. Yamins, Nicolas Pinto, Diego Ardila, Ethan A. Solomon, Najib J. […]

PNAS paper out on the HMO model results

PNAS paper out on the HMO model results

May 15, 2014

Dan Yamins’ paper on predicting higher visual cortex responses with the HMO model is out in PNAS! You can find it here: early access Daniel L. K. Yamins, Ha Hong, Charles F. Cadieu, Ethan A. Solomon, Darren Seibert, and James J. DiCarlo. Performance-optimized hierarchical models predict neural responses in higher visual cortex.  PNAS 2014 111 (23) […]

Deep Conv. Nets Similar to IT and Human Ventral Stream (NIPS 2013 paper)

Deep Conv. Nets Similar to IT and Human Ventral Stream (NIPS 2013 paper)

Dec 9, 2013

Dan Yamins and Ha Hong led the effort for this paper from the DiCarlo lab.  Some very promising results! Daniel L Yamins, Ha Hong, Charles Cadieu, James J DiCarlo. Hierarchical Modular Optimization of Convolutional Networks Achieves Representations Similar to Macaque IT and Human Ventral Stream Get the paper here.  

IQ Engines + Flickr/Yahoo!

IQ Engines + Flickr/Yahoo!

Aug 26, 2013

A great day for the IQ Engines team!  The company has been acquired by Yahoo! to improve the Flickr experience.  It has been a great privilege to be part of IQ Engines from the beginning.  I’m excited to see how they use their great technology to bring Flickr to the next level! See it on […]

Glow… coming soon.

Glow… coming soon.

Aug 1, 2013

Over at IQ Engines, our great team is putting together a new mobile app called Glow.  It’s been great fun to use it first hand and it has provided a whole new dimension to my photos.  Here’s the blurb from our website: Glow is an image recognition platform that automatically tags photos. It recognizes scenes, […]

Video of ICLR 2013 Talk Posted

Video of ICLR 2013 Talk Posted

Jul 12, 2013

You can watch the talk here: talk, with many great questions from an exciting group of researchers. The Neural Representation Benchmark and its Evaluation on Brain and Machine Charles F. Cadieu, Ha Hong, Dan Yamins, Nicolas Pinto, Najib J, Majaj, James J. DiCarlo

Upcoming talk at ICLR 2013

Upcoming talk at ICLR 2013

Apr 30, 2013

I will be presenting some recent work at the new International Conference on Learning Representations.  The conference has an innovative submission and review format.  You can find our submitted conference paper here, and the open reviews here.

SmartAlbum from IQ Engines

SmartAlbum from IQ Engines

Mar 27, 2013

An exciting new product from IQ Engines using image intelligence to organize your photos! See the post: http://blog.iqengines.com/post/45843716516/smartalbum-adds-face-detection-and-recognition and try it for yourself: http://www.iqengines.com/smartalbum  

Talk at Cosyne 2013

Talk at Cosyne 2013

Mar 5, 2013

I just arrived back from Cosyne where I presented our work on “A neural encoding model of PL, the earliest face selective region in monkey IT.”  This is work with Elias Issa and Jim DiCarlo @ MIT. We received a very positive response to our work.  As it is early days for this project, in the […]

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