[N] HGX-2 Deep Learning Benchmarks: The 81,920 CUDA Core “Behemoth” GPU Server

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Deep learning benchmarks for TensorFlow on Exxact TensorEX HGX-2 Server. Original Post from Exxact Here Notable GPU Server Features 16x NVIDIA Tesla V100 SXM3 81,920 NVIDIA CUDA Cores 10,240 NVIDIA Tensor Cores .5TB Total GPU Memory NVSwitch powered by NVLink 2.4TB/sec aggregate speed Source: blog.exxactcorp.com Source: blog.exxactcorp.com Tests were run […]

[P] Towards explainable video analysis – Visual Attention For Action Recognition

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​ I am currently researching practical applications of action recognition models with use of attention models. I have decided to share lessons learned from implementing several ideas from research papers in this field. The network learns to classify images from HMDB-51 dataset and creates attention heatmaps which focus on different […]

[Project] `gpt2-client`: A New Wrapper for GPT-2

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Hey everyone 👋🏻 I recently built a wrapper for OpenAI's `gpt-2` model called `gpt2-client`. Currently, the `gpt-2` repo is archived and the code is messy and riddled with bugs. My wrapper simplifies the entire process by enabling anyone to get started with text generation models without the fuss. ​ It […]

[P] Web-based implementation of Deep Image Prior

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https://warlock.ai/deepimageprior/ Using TensorFlow.js I implemented a client-side version of Deep Image Prior. It can be used for denoising, inpainting, super-resolution (not implemented yet) and more. It works by training a network to output a given image. More info about the algorithm can be found on the original authors' project page. […]

[Research] Temporal Attentive Alignment for Large-Scale Video Domain Adaptation (ICCV 2019 Oral)

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Hello, It's my pleasure to share our recent work on Video Domain Adaptation with you! We proposed large-scale cross-domain action datasets, and developed an attention-based spatio-temporal DA mechanism to achieve effective domain alignment. ​ Temporal Attentive Alignment for Large-Scale Video Domain Adaptation (ICCV 2019 Oral) [GitHub] https://github.com/cmhungsteve/TA3N [arXiv] https://arxiv.org/abs/1907.12743 ​ […]

[D] Two questions about deep q learning

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​ https://i.redd.it/9eifb59zaoe31.png I have two questions(In bold) I want to use two neural networks to calculate the Q value for my current state(A board game). I use a sigmoid function. I correct the action with the highest value max Q that I obtain in the target network(The rest target is […]

How to Develop a Pix2Pix GAN for Image-to-Image Translation

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The Pix2Pix Generative Adversarial Network, or GAN, is an approach to training a deep convolutional neural network for image-to-image translation tasks. The careful configuration of architecture as a type of image-conditional GAN allows for both the generation of large images compared to prior GAN models (e.g. such as 256×256 pixels) […]

[P] MachinesGoneWrong – a primer to algorithmic bias

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Hey all, am a graduate student working on AI and AI ethics. As part of a 3-month final project, I built an online primer/beginner's guide to algorithmic bias. It contains: – xkcd-style comics (a tribute and thanks to the esteemed Randall Munroe!) – an explorable for fairness definitions – a […]

[R] [1907.10830] U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation

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​ 1st row : input, 2nd row : attention map, 3rd row : output Each column dataset is "selfie2anime", "horse2zebra", "cat2dog", "photo2vangogh", "photo2portrait" & "portrait2photo", "vangogh2photo", "dog2cat", "zebra2horse", "anime2selfie" Abstract We propose a novel method for unsupervised image-to-image translation, which incorporates a new attention module and a new learnable normalization […]