“"docTR" (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by #Deep-Learning.” Apache2. This is what Famine- is using for their #OCR project. #toread
on 02026-04-22kind of disturbing #porn thread using #deep-learning #neural-networks to convert ordinary photos of women into realistic nudes
on 02025-04-12commentary on #deep-learning video from text system "Make-A-Video" makeavideo.studio
on 02022-09-29code for #deep-learning of #truss #metamaterials
on 02022-02-09#deep-learning of #truss #metamaterials to instantly generate designs with a given anisotropic #stiffness tensor. #CC-BY
on 02022-02-09note on ASIC #hardware for #deep-learning #neural-networks, snapshot of https://blog.inten.to/hardware-for-deep-learning-part-4-asic-96a542fe6a81
on 02021-01-24Alexander Rush talks about how “tensors” in the style of #APL are central to PyTorch (#Torch-7) and proposes what he thinks is a better API. #deep-learning
on 02019-01-21Bitmain moves from #Bitcoin into #deep-learning. Jihan Wu has a degree in psychology and economics from Peking University.
on 02017-09-13A #paper on “imitation learning” in #robotics with #deep-learning
on 02017-08-06Successful cryptanalysis of Enigma with recurrent #neural-networks. #crypto #deep-learning
on 02017-08-06#Deep-learning for a kinematic problem as an example of a poorly-specified problem
on 02017-07-31Tensor2Tensor is a new #deep-learning library I don’t understand. “With T2T you can approach previous state-of-the-art results with a single GPU in one day.”)http://www.newyorker.com/magazine/2017/06/26/chinas-mistress-dispellers “Mistress dispellers”. #China
on 02017-07-01#Deep-learning #neural-networks from scratch in #R, with IPython/#Jupyter notebooks
on 02017-07-01a #deep-learning library for #Clojure
on 02017-05-09The first chapter of the famed "UFLDL Tutorial" #ebook (“Unsupervised Feature Learning and Deep Learning”) on #machine-learning covers linear regression; later it covers #deep-learning and other #neural-networks.
on 02017-01-14Ian Goodfellow’s #ebook on #deep-learning #neural-networks; supposedly the most comprehensive available. Goodfellow is the guy who invented GANs I think. #machine-learning
on 02017-01-03suggested avenues for learning about #deep-learning, including recommendations of software, etc.
on 02017-01-03“practical #deep-learning for coders” MOOC
on 02016-12-21Intel tries to get ahead of the #deep-learning #hardware curve by acquiring Nervana and Movidius. #finance #business
on 02016-10-17#deep-learning #introduction: “[The] [t]op [5] deep learning papers on arXiv are presented, summarized, and explained with the help of a leading researcher in the field.” #toread
on 02016-10-11#paper on #DCGANs (variety “introspective adversarial networks”) for photo editing. #deep-learning #neural-networks #GANs #machine-learning
on 02016-10-03#deep-learning #neural-networks with #tensorflow for low-cost #robotics
on 02016-09-23#Tutorial on #TensorFlow #deep-learning to do #OCR of handwritten digits
on 02016-09-02an update on the state of the art of #reinforcement-learning by #Karpathy. #AI #deep-learning #machine-learning #toread
on 02016-06-21"Inceptionism" pictures: combining different images using #deep-learning #neural-networks in the style of Deep Dream.
on 02016-06-02“Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks”, by Alec Radford, Luke Metz, and Soumith Chintala, generated realistic images of bedrooms with convolutional #deep-learning #neural-networks by simultaneously training two networks in a sort of Turing test: one that tried to generate realistic images of bedrooms and one that tried to distinguish between the real images and fake ones. They call this technique "DCGANs". #GANs #machine-learning
on 02016-05-24a #history of #deep-learning, with lots of pictures and a good explanation of the Perceptron and how it led to modern #neural-networks. With pictures and video segments and whatnot.
on 02016-04-25Lecture notes for a Stanford class on #neural-networks and #deep-learning, written by Andrej #Karpathy, the author of #unreasonable-RNNs.
on 02016-04-25An #ebook introduction to #neural-networks and #deep-learning.
on 02016-04-25Pete Warden ported the Deep Belief #deep-learning #neural-networks for #image-recognition to #Raspberry-Pi #GPGPU.
on 02016-04-16using FindFace #deep-learning #neural-networks to do #face-recognition #image-recognition of photos of random people he meets on the subway. #privacy
on 02016-04-16Some starting points for #deep-learning and recursive #neural-networks.
on 02016-03-29an overview of the last year’s worth of #deep-learning breakthroughs and some advocacy of a universal #basic-income guarantee. #economics #politics
on 02016-03-19Leaf is a #machine-learning #deep-learning #neural-networks system in Rust.
on 02016-03-08Brad Neuberg walks through his experience writing a #deep-learning #neural-networks system for face recognition.
on 02016-02-11“a Python and #Torch-7 implementation of #face-recognition with #deep-learning #neural-networks”
on 02016-01-19Jeff Dean’s talk about #deep-learning in general and #TensorFlow on 2015-10-22, before its release. He explains how important #automatic-differentiation is to them and mentions Theano.
on 02016-01-11Song Han’s new “EIE” #hardware for running #deep-learning #neural-networks with compressed (pruned and 5-bit-quantized) weights in on-chip SRAM runs “between 13× and 189× faster over regular CPU and also GPU implementations” and “the energy efficiency is better by between 3,000× on a GPU and 24,000× on CPU”. It’s very interesting to see an improvement of three orders of magnitude over the state of the art, particularly since what made deep learning practical over the last three or so years is in significant part (?) a single order of magnitude improvement in processing power. I’m not clear on whether this improvement exists for training as well (where you might not be able to get away with 5-bit weights), or just for inference.
on 02016-01-11a brief comparison of #TensorFlow, Facebook’s Ronan Collobert’s faster #Torch-7, the Caffe convnets library, and Yoshua Bengio’s #Theano. “Just as a Tesla is yet another four-wheeled conveyance with four doors, a steering wheel and a roof, TensorFlow appears to be the best, most convenient library for #deep-learning, more worthy of anointment.”
on 02016-01-11“To Recognize Shapes, First Learn to Generate Images” with #neural-networks #deep-learning with a history of perceptrons and whatnot (as of 2006, just before the deep learning revolution)
on 02015-08-05