Search results for Generative Adversarial Network

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  • Generative Adversarial Networks – Paper Reading Road Map

    ...more about the technical sides of GANs, I wanted to share some papers I have read in the order that I read them. For a less technical introduction to Generative Adversarial Networks, have a look at here. Before reading these papers, I recommend you to revise the basics of deep learning if you are...

    https://www.kdnuggets.com/2018/10/generative-adversarial-networks-paper-reading-road-map.html

  • Generative Adversarial Networks, an overview

    ...ating images. The following is the outline of this article A brief review of Deep Learning The image generation problem Key issue in generative tasks Generative Adversarial Networks Challenges Further reading Conclusion   Sketch of a (feed-forward) neural network, with input layer in brown,...

    https://www.kdnuggets.com/2018/01/generative-adversarial-networks-overview.html

  • Intro to Adversarial Machine Learning and Generative Adversarial Networks

    ...ng, when we talk about generative models, we’re usually talking about one of four kinds of models: Autoregressive Reversible Variational Autoencoders Generative Adversarial Networks Autoregressive models: With autoregressive models, you generate an image by generating each pixel conditioned on the...

    https://www.kdnuggets.com/2019/10/adversarial-machine-learning-generative-adversarial-networks.html

  • The Rise of Generative Adversarial Networks

    ...ck, Generative Adversarial Networks(GANs) started a revolution in deep learning. This revolution has produced some major technological breakthroughs. Generative Adversarial Networks were introduced by Ian Goodfellow and others in the paper titled “Generative Adversarial Networks” —...

    https://www.kdnuggets.com/2019/04/rise-generative-adversarial-networks.html

  • Deep Learning Research Review: Generative Adversarial Nets

    ...be looking at 3 papers that built on the pioneering work of Ian Goodfellow in 2014. Quick Summary of GANs   I briefly mentioned Ian Goodfellow’s Generative Adversarial Network paper in one of my prior blog posts, 9 Deep Learning Papers You Should Know About. The basic idea of these networks is...

    https://www.kdnuggets.com/2016/10/deep-learning-research-review-generative-adversarial-networks.html

  • Graduating in GANs: Going From Understanding Generative Adversarial Networks to Running Your Own

    ...generates become increasingly realistic as training progresses!   Brief primer on GANs   Since its inception in 2014 with Ian Goodfellow’s ‘Generative Adversarial Networks’ paper, progress with GANs has exploded and led to increasingly realistic outputs. 4.5 years of GAN progress on face...

    https://www.kdnuggets.com/2019/04/graduating-gans-understanding-generative-adversarial-networks.html

  • Research Guide for Video Frame Interpolation with Deep Learning

    ...as the optimization strategy. The results obtained are shown below. source     Frame Interpolation with Multi-Scale Deep Loss Functions and Generative Adversarial Networks (2019)   In this paper, the authors propose a multi-scale generative adversarial network for frame interpolation...

    https://www.kdnuggets.com/2019/10/research-guide-video-frame-interpolation-deep-learning.html

  • Generative Adversarial Networks – Key Milestones and State of the Art

    ...earn. After that, we’ll examine two promising GANs: the RadialGAN,[2]which is designed for numbers, and the StyleGAN, which is focused on images. The Generative Adversarial Network (GAN) The original GAN[3] was created by Ian Goodfellow, who described the GAN architecture in a paper published in...

    https://www.kdnuggets.com/2019/04/future-generative-adversarial-networks.html

  • Generative Adversarial Neural Networks: Infinite Monkeys and The Great British Bake Off

    ...o see if they have written Shakespeare (or anything good) is called a Discriminator. These are the two components of an Generative Adversarial Neural Network. Adversarial Neural Networks are oddly named since they actually cooperate to make things. Cooks in the Kitchen: I am obsessed with the TV...

    https://www.kdnuggets.com/2018/05/generative-adversarial-neural-networks-infinite-monkeys-great-british-bake-off.html

  • Deep Learning, Generative Adversarial Networks  & Boxing – Toward a Fundamental Understanding

    ...problem as a game between the two. In this post we will see why GANs have so much potential, and frame GANs as a boxing match between two opponents. Generative adversarial networks aren’t so different 👊. Intuition behind deep learning   Deep learning is famously biologically inspired and many...

    https://www.kdnuggets.com/2017/03/deep-learning-gans-boxing-fundamental-understanding.html

  • 9 Key Deep Learning Papers, Explained">Gold Blog9 Key Deep Learning Papers, Explained

    ...for the output volume. The way that the authors address this is by adding 1x1 conv operations before the 3x3 and 5x5 layers. The 1x1 convolutions (or network in network layer) provide a method of dimensionality reduction. For example, let’s say you had an input volume of 100x100x60 (This isn’t...

    https://www.kdnuggets.com/2016/09/9-key-deep-learning-papers-explained.html

  • MNIST Generative Adversarial Model in Keras

    By Tim O'Shea, O'Shea Research. Some of the generative work done in the past year or two using generative adversarial networks (GANs) has been pretty exciting and demonstrated some very impressive results. The general idea is that you train two models, one (G) to generate some sort of output...

    https://www.kdnuggets.com/2016/07/mnist-generative-adversarial-model-keras.html

  • Only Numpy: Implementing GANs and Adam Optimizer using Numpy">Silver BlogOnly Numpy: Implementing GANs and Adam Optimizer using Numpy

    ...f you are interested.   References Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., … & Bengio, Y. (2014). Generative adversarial nets. In Advances in neural information processing systems (pp. 2672–2680). Free Online Animated GIF Maker — Make GIF Images...

    https://www.kdnuggets.com/2018/08/only-numpy-implementing-gans-adam-optimizer.html

  • Top 5 Deep Learning Resources, January

    ...is an interesting read, especially if you are a fan of the recent deep generative works such as Inceptionism, Deep Forger, or the deep convolutional generative adversarial networks (DCGANs) paper immediately below. 2. Unsupervised Representation Learning with Deep Convolutional Generative...

    https://www.kdnuggets.com/2016/01/deep-learning-reading-list-january.html

  • Overview of GANs (Generative Adversarial Networks) – Part I

    ...the training problems as well as make big improvements in realistic image generation. Original. Reposted with permission. Related: Overview of GANs (Generative Adversarial Networks) Part I Capsule Networks are Shaking Up AI-Here's How to Use Them Top 10 Videos on Deep Learning in Python  ...

    https://www.kdnuggets.com/2017/11/overview-gans-generative-adversarial-networks-part1.html

  • CAN (Creative Adversarial Network) - Explained

    …e value of Equation 1.4 as small as possible by Maximizing the value of A more detailed explanation can be found at http://wiki.ubc.ca/Course:CPSC522/Generative_Adversarial_Networks Intuitive definition The Generator will try to modify itself to make the Discriminator pass its own creation as real,…

    https://www.kdnuggets.com/2017/07/creative-adversarial-network.html

  • The New Neural Internet is Coming

    ...neural networks (such as image classifier) as a left hemisphere of the neural network technology. With this in mind, it is easy to understand what is Generative Adversarial Network. It is a kind of right hemisphere — the one that is claimed to be responsible for creativity. The Generative...

    https://www.kdnuggets.com/2018/02/new-neural-internet-coming.html

  • Generative Adversarial Networks – Hot Topic in Machine Learning

    …Nothing to complain about. Original. Reposted by Permission. Bio: Al Gharakhanian is well-rounded executive with extensive experience in Product Marketing, Sales, and Business Development in Semiconductors, Machine Learning, and Data Science. Related: Deep Learning Research Review: Generative

    https://www.kdnuggets.com/2017/01/generative-adversarial-networks-hot-topic-machine-learning.html

  • Top arXiv Papers, January: ConvNets Advances, Wide Instead of Deep, Adversarial Networks Win, Learning to Reinforcement Learn

    ...on ImageNet. Our code and models are available at this https URL Adversarial Feature Learning   Jeff Donahue, Philipp Krähenbühl, Trevor Darrell Generative Adversarial Networks (GANs) are a "hot topic" in machine learning. GANs do a great job mapping simple latent data distributions to more...

    https://www.kdnuggets.com/2017/02/top-arxiv-papers-january-convnets-wide-adversarial.html

  • Age of AI Conference 2018 – Day 1 Highlights

    ...tent. Here are the highlights of Day 1, Wednesday, January 31.   Balaji Laxminarayanan, Senior Research Scientist, DeepMind   Understanding Generative Adversarial Networks Key Points: This talk delves into some theory behind Generative Adversarial Networks (GANs). How do GANs relate to...

    https://www.kdnuggets.com/2018/02/age-ai-conference-2018-day-1.html

  • Which Face is Real?

    ...They created the StyleGAN. To learn a little more about this amazing technique, I have provided some resources and concise explanations below.   Generative Adversarial Network   For those wanting a refresher on GAN's, this playlist of tutorials on GAN's by Ahlad Kumar is quite helpful....

    https://www.kdnuggets.com/2019/04/which-face-real-stylegan.html

  • InfoGAN - Generative Adversarial Networks Part III

    ...urity and effectiveness. If you find a particular paper you’d like reviewed here, feel free to drop a note in the comments. Related Overview of GANs (Generative Adversarial Networks) – Part I Generative Adversarial Networks — Part II Understanding deep Convolutional Neural Networks with a practical...

    https://www.kdnuggets.com/2017/11/infogan-generative-adversarial-networks-part3.html

  • 6 areas of AI and Machine Learning to watch closely">Gold Blog6 areas of AI and Machine Learning to watch closely

    …f similar faces. For more details on how these models work, see Ian Goodfellow’s awesome NIPS 2016 tutorial write up. The architecture he introduced, generative adversarial networks (GANs), are particularly hot right now in the research world because they offer a path towards unsupervised learning….

    https://www.kdnuggets.com/2017/01/6-areas-ai-machine-learning.html

  • The Major Advancements in Deep Learning in 2016

    ...o data representation that can be useful for clustering, dimensionality reduction, improving supervised classification and even for data compression. Generative Adversarial Networks (GANs)   Recently, a new approach based on generative models has emerged. Called Generative Adversarial...

    https://www.kdnuggets.com/2017/01/major-advancements-deep-learning-2016.html

  • My favorite mind-blowing Machine Learning/AI breakthroughs">Silver BlogMy favorite mind-blowing Machine Learning/AI breakthroughs

    ...icial faces that are interpolations between other faces or applications of the “style” of one face to another face. The work builds upon past work on Generative Adversarial Networks (GANs). GANs were invented in 2014 and have seen an explosion in research since then. The most basic concept of GANs...

    https://www.kdnuggets.com/2019/03/favorite-ml-ai-breakthroughs.html

  • Generative Adversarial Networks — Part II

    ...e “latent code” from the noise, then generators would be more useful since you could control the output systematically and reliably without having to randomly walk the space. This problem and solution will be explored in Part III. Original. Reposted with permission. Related: Can (Creative...

    https://www.kdnuggets.com/2017/11/generative-adversarial-networks-part2.html

  • Deep Learning Research Review: Reinforcement Learning

    ...g in Bioinformatics at UCLA. He is passionate about applying his knowledge of machine learning and computer vision to areas in healthcare where better solutions can be engineered for doctors and patients. Original. Reposted with permission. Related: Deep Learning Research Review: Generative...

    https://www.kdnuggets.com/2016/11/deep-learning-research-review-reinforcement-learning.html

  • Deep Stubborn Networks – A Breakthrough Advance Towards Adversarial Machine Intelligence">Silver Blog, Apr 2017Deep Stubborn Networks – A Breakthrough Advance Towards Adversarial Machine Intelligence

    ...as extent variable modeling. This technique is enough to cause massive confusion for the discriminator, and leads to soaring error rate levels in the generative network. Once this occurs, both networks become overwhelmed, leading to a human-like condition similar to The Paradox of Choice. With both...

    https://www.kdnuggets.com/2017/04/deep-stubborn-networks-gan-refinement.html

  • Are Deep Neural Networks Creative?

    ...ingen in Germany, can extract the style from one image (say a painting by Van Gogh), and apply it to the content of another image (say a photograph). Generative adversarial networks (GANs), introduced by Ian Goodfellow, are capable of synthesizing novel images by modeling the distribution of seen...

    https://www.kdnuggets.com/2016/05/deep-neural-networks-creative-deep-learning-art.html

  • Interpolation in Autoencoders via an Adversarial Regularizer

    ...ure and its training, allowing the autoencoder to learn the underlying data manifold and to create meaningful interpolations. By borrowing ideas from Generative Adversarial Networks (Goodfellow et al., 2014), ACAI effectively integrates the interpolation process into the autoencoder architecture....

    https://www.kdnuggets.com/2019/03/interpolation-autoencoders-adversarial-regularizer.html

  • Deep Learning for NLP: An Overview of Recent Trends">Silver BlogDeep Learning for NLP: An Overview of Recent Trends

    ...d in previous language modeling techniques.   Deep Generative Models   Deep generative models, such as variational autoenconders (VAEs) and generative adversarial networks (GANs), are also applied in NLP to discover rich structure in natural language through the process of generating...

    https://www.kdnuggets.com/2018/09/deep-learning-nlp-overview-recent-trends.html

  • First Steps of Learning Deep Learning: Image Classification in Keras

    ...eural Algorithm of Artistic Style style transfer (and for videos!) Real-time Face Capture and Reenactment Colorful Image Colorization Plug & Play Generative Networks for photorealistic image generation Dermatologist-level classification of skin cancer along with other medical diagnostic tools...

    https://www.kdnuggets.com/2017/08/first-steps-learning-deep-learning-image-classification-keras.html

  • Top /r/MachineLearning Posts, November: TensorFlow, Deep Convolutional Generative Adversarial Networks, and lolz

    ...of the system (with some foreshadowing of its recent big news). Find the video below. 5. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks +173 Generative adversarial networks creating their own image representations. I won't give away much more than that....

    https://www.kdnuggets.com/2015/12/top-reddit-machine-learning-november.html

  • Deep Learning Transcends the Bag of Words

    ...models repurpose convolutional neural nets, which are traditionally discriminative models, to generate images. Also of interest are recent papers on generative adversarial learning, which learn to generate images such that they fool a discriminative model trained to distinguish between real and...

    https://www.kdnuggets.com/2015/12/deep-learning-outgrows-bag-words-recurrent-neural-networks.html

  • ICLR 2019 highlights: Ian Goodfellow and GANs, Adversarial Examples, Reinforcement Learning, Fairness, Safety, Social Good, and all that jazz

    ...ture prediction as a sequential decision making process and focused on papers that leverage the advances in deep RL to improve structured prediction. Generative Adversarial Models and Adversarial Examples Besides Goodfellow’s keynote talk, which focused on GAN’s applications to different ML...

    https://www.kdnuggets.com/2019/05/iclr-2019-highlights.html

  • Cooperative Trust Among Neural Networks Drives Deeper Learning

    ...s the feeding forward of an authentic-seeming faux pattern or other digital object (eg., photo) that was generated by one neural network (called the “generative network”) for ingest by another neural network (called the “discriminative network”). The former network relies on supervised learning in...

    https://www.kdnuggets.com/2017/02/ibm-cooperative-trust-neural-networks-deeper-learning.html

  • More Deep Learning “Magic”: Paintings to photos, horses to zebras, and more amazing image-to-image translation

    ...rks). Collection style transfer. The following is from the abstract of the authors' paper, Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks: Image-to-image translation is a class of vision and graphics problems where the goal is to learn the mapping between an input...

    https://www.kdnuggets.com/2017/04/unpaired-image-translation-cycle-gan.html

  • 7 Steps to Understanding Deep Learning

    ...ctive Boltzmann Machines are an obvious exclusion which comes to mind, as are autoencoders, and a whole series of related generative models including Generative Adversarial Networks. However, a line had to be drawn somewhere, or this post would continue ad infinitum. For those interested in...

    https://www.kdnuggets.com/2016/01/seven-steps-deep-learning.html

  • State of Deep Learning and Major Advances: H2 2018 Review

    ...re. The library has over 8,000 stars on GitHub. Most activity: NLP and GANs Looking at the top fifty implementations, the hottest fields appear to be generative methods and natural language processing (NLP). Within generative methods, popular implementations on GitHub included: vid2vid, DeOldify,...

    https://www.kdnuggets.com/2018/12/deep-learning-major-advances-review.html

  • A Summary of DeepMind’s Protein Folding Upset at CASP13">Silver BlogA Summary of DeepMind’s Protein Folding Upset at CASP13

    ...es were actually a result of gradient descent optimization. The DeepMind team tried a ‘fancier’ strategy involving fragment assembly using Generative Adversarial Networks (GANs), but in the end, the best results were obtained by gradient descent optimization. Gradient descent was applied to a...

    https://www.kdnuggets.com/2019/07/deepmind-protein-folding-upset.html

  • Beyond the Fence, and the Advent of the Creative Machines

    ...sic composition has been undertaken in the recent past by different learning algorithms, including Restricted Boltzmann Machines and Recurrent Neural Networks. Generative neural networks have become a part of the rich deep learning research landscape. Online searches turn up new models weekly, be...

    https://www.kdnuggets.com/2016/01/beyond-fence-advent-creative-machines.html

  • How to Organize Data Labeling for Machine Learning: Approaches and Tools

    ...r. Synthetic data is produced by a generative model that is trained and validated on an original dataset. There are three types of generative models: Generative Adversarial Networks (or GANs), Autoregressive models (ARs), and Variational Autoencoders (VAEs). Generative Adversarial Networks. GAN...

    https://www.kdnuggets.com/2018/05/data-labeling-machine-learning.html

  • KDnuggets™ News 19:n17, May 1: The most desired skill in data science; Seeking KDnuggets Editors, work remotely

    ...uating in GANs: Going From Understanding Generative Adversarial Networks to Running Your Own Normalization vs Standardization - Quantitative analysis Generative Adversarial Networks - Key Milestones and State of the Art Attention Craving RNNS: Building Up To Transformer Networks   Opinions The...

    https://www.kdnuggets.com/2019/n17.html

  • GANs in TensorFlow from the Command Line: Creating Your First GitHub Project

    ...sis management, as CEO and Data Scientist in the areas of strategic planning and restructuring, physical and digital marketing, social networks analysis, personnel management, customer database analysis. He has 13 years of Market Research expertise and 10 years of data analysis experience. Related:...

    https://www.kdnuggets.com/2018/05/zimbres-first-github-project-gans.html

  • KDnuggets™ News 19:n16, Apr 24: Data Visualization in Python with Matplotlib & Seaborn; Getting Into Data Science: The Ultimate Q&A

    ...Part 2: Setting your DataOps Environment Top KDnuggets tweets, Apr 10-16: Math for Programmers teaches you the #math you need to know; The Third Wave Data Scientist - what skills are required?    Image of the week From The Rise of Generative Adversarial Networks...

    https://www.kdnuggets.com/2019/n16.html

  • KDnuggets™ News 18:n41, Oct 31: Introduction to Deep Learning with Keras; Easy Named Entity Recognition with Scikit-Learn

    ...he latest KDnuggets poll, How Important is Understanding Machine Learning Models?   Features Introduction to Deep Learning with Keras Generative Adversarial Networks - Paper Reading Road Map New Poll: How Important is Understanding Machine Learning Models? Named Entity Recognition and...

    https://www.kdnuggets.com/2018/n41.html

  • Yann LeCun Quora Session Overview

    ...in deep learning? LeCun first selects one exemplar breakthrough. The most important one, in my opinion, is adversarial training (also called GAN for Generative Adversarial Networks). This is an idea that was originally proposed by Ian Goodfellow when he was a student with Yoshua Bengio at the...

    https://www.kdnuggets.com/2016/08/yann-lecun-quora-session.html

  • Top /r/MachineLearning Posts, April: Why Momentum Really Works; Machine Learning with Scikit-Learn & TensorFlow

    ...new book from O'Reilly on machine learning with Scikit-Learn and TensorFlow, find out about a self-driving car course, have some fun with generative adversarial networks, explore the mysteries of Go, and read about DeepMind solving AGI... and summoning the demons. The top /r/MachineLearning posts...

    https://www.kdnuggets.com/2017/05/top-reddit-machine-learning-april.html

  • Artificial Intelligence and Data Science Advances in 2018 and Trends for 2019

    ...perceptron (MLP), neural net training techniques like backpropagation and backpropagation through time (BPTT), residual networks, the introduction of Generative Adversarial Networks (GANs), and deep Q-learning networks (DQN). ”So, looking back to memorable ones I listed before, there weren’t ‘brand...

    https://www.kdnuggets.com/2019/02/ai-data-science-advances-trends.html

  • Top 20 Deep Learning Papers, 2018 Edition">Gold BlogTop 20 Deep Learning Papers, 2018 Edition

    ...atConvNet and gives the technical details of each computational block in the toolbox. 9. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks , by Alec R., Luke M. & Soumith C. (2015) (Cited: 1,054) In this work, we hope to help bridge the gap between the...

    https://www.kdnuggets.com/2018/03/top-20-deep-learning-papers-2018.html

  • AI Masterpieces: But is it Art?

    ...e room for the concept of art itself, even calling it “… more of a parlor trick than the next revolution in fine art.” comments Image synthesis using generative adversarial networks   Robbie Barrat, now a researcher at Stanford, had the idea of using generative adversarial networks (GANs) to...

    https://www.kdnuggets.com/2018/10/ai-art.html

  • Research Guide: Advanced Loss Functions for Machine Learning Models

    ...loss function are able to generate higher quality images than regular GANs. A comparison of the two is shown in the next figure. NIPS 2016 Tutorial: Generative Adversarial Networks This report summarizes the tutorial presented by the author at NIPS 2016 on generative adversarial networks (GANs)....

    https://www.kdnuggets.com/2019/11/research-guide-advanced-loss-functions-machine-learning-models.html

  • Recent Advances for a Better Understanding of Deep Learning">Silver BlogRecent Advances for a Better Understanding of Deep Learning

    ...zation? Role of Depth: How does depth help a neural network to converge? What is the link between depth and generalization? Generative Models: Why do Generative Adversarial Networks (GANs) work so well? What theoretical properties could we use to stabilize them or avoid mode collapse? In this...

    https://www.kdnuggets.com/2018/10/recent-advances-deep-learning.html

  • A “Weird” Introduction to Deep Learning">Silver BlogA “Weird” Introduction to Deep Learning

    ...constant. This argument is required if you are… BTW: It was shown by Liao and Poggio (2016) that ResNets == RNNs, arXiv:1604.03640v1.   9. Idea: Generative Adversarial Networks (GANs). [1406.2661v1] Generative Adversarial Networks Abstract: We propose a new framework for estimating generative...

    https://www.kdnuggets.com/2018/03/weird-introduction-deep-learning.html

  • Using Deep Learning to Solve Real World Problems">Gold BlogUsing Deep Learning to Solve Real World Problems

    ...sking for sophisticated solutions such as generating text, transforming images, and custom object detection. We are exploring Reinforcement Learning, Generative Adversarial Nets, and Bayesian Casual Inference. The tools are now widely available and free. Machine learning is no longer a software...

    https://www.kdnuggets.com/2017/12/using-deep-learning-solve-real-world-problems.html

  • A comprehensive survey on graph neural networks

    ...Networks. Graph Auto-encoders combine the familiar encoder-decoder pairs, but using graph representations on both sides. Finally, the class of Graph Generative Networks aim to generate plausible structures from data. The following table highlights some of the key approaches in these extended...

    https://www.kdnuggets.com/2019/02/comprehensive-survey-graph-neural-networks.html

  • How GOAT Taught a Machine to Love Sneakers

    ...h a Constrained Variational Framework Understanding disentangling in β-VAE Wasserstein Auto-Encoders Visualizing Data using t-SNE Sampling Generative Networks Generative Adversarial Networks Original. Reposted with permission. Related: Deep Learning, The Curse of Dimensionality, and Autoencoders...

    https://www.kdnuggets.com/2018/08/goat-taught-machine-love-sneakers.html

  • Top Data Science and Machine Learning Methods Used in 2017">Gold BlogTop Data Science and Machine Learning Methods Used in 2017

    ....4% Conv Nets, 15.8% Recurrent Neural Networks (RNN), 10.5% Hidden Markov Models (HMM), 4.6% Reinforcement Learning, 4.2% Markov Logic Networks, 2.5% Generative Adversarial Networks (GAN), 2.3% The largest decline in share of usage was for Singular Value Decomposition (SVD), 48% down, from 15.4%...

    https://www.kdnuggets.com/2017/12/top-data-science-machine-learning-methods.html

  • Top 20 Recent Research Papers on Machine Learning and Deep Learning">Silver Blog, 2017Top 20 Recent Research Papers on Machine Learning and Deep Learning

    ...e new methods to compare the density and diversity of image datasets and show that Places is as dense as other scene datasets and has more diversity. Generative adversarial nets, by Bengio, Y., Courville, A.C., Goodfellow, I.J., Mirza, M., Ozair, S., Pouget-Abadie, J., Warde-Farley, D., & Xu,...

    https://www.kdnuggets.com/2017/04/top-20-papers-machine-learning.html

  • Awesome Deep Learning: Most Cited Deep Learning Papers">Gold Blog, Apr 2017Awesome Deep Learning: Most Cited Deep Learning Papers

    ...ovariate shift (2015), S. Loffe and C. Szegedy [pdf] 3. Unsupervised / Generative Models Unsupervised representation learning with deep convolutional generative adversarial networks (2015), A. Radford et al. [pdf] 4. Convolutional Neural Network Models Deep residual learning for image recognition...

    https://www.kdnuggets.com/2017/04/awesome-deep-learning-most-cited-papers.html

  • 10 New Things I Learnt from fast.ai Course V3

    ...and generating embeddings. Some experience of the following would be great too: image classification, text classification, semantic segmentation and generative adversarial networks. I organised the content of my 10 learning points as such: from the theory of neural networks, to architectures, to...

    https://www.kdnuggets.com/2019/06/things-learnt-fastai-course.html

  • What You Are Too Afraid to Ask About Artificial Intelligence (Part I): Machine Learning

    ...., Duan, X., Houthooft, R., Schulman, J., Sutskever, I., Abbeel, P. (2016). “InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets”. arXiv:1606.03657. Giustolisi, O., Savic, D.A. (2006). “A symbolic data-driven technique based on evolutionary...

    https://www.kdnuggets.com/2016/12/too-afraid-ask-about-artificial-intelligence-machine-learning.html

  • The Five Capability Levels of Deep Learning Intelligence

    ...jectives. We actually do se primitive versions of this in adversarial networks, that learn to perform generalization with competing discriminator and generative networks Expand that concept further into game-theoretic driven networks that are able to perform strategically and tactically solving...

    https://www.kdnuggets.com/2016/12/5-capability-levels-deep-learning-intelligence.html

  • Machine Learning & AI Main Developments in 2018 and Key Trends for 2019">Gold BlogMachine Learning & AI Main Developments in 2018 and Key Trends for 2019

    ...eded or are standard, raw data is close to what the machine expects as the input, and the data is in abundance). 2) Marketing automation: with mature generative adversarial networks and variational autoencoders it is becoming possible to generate thousands of pictures of the same person or paysage...

    https://www.kdnuggets.com/2018/12/predictions-machine-learning-ai-2019.html

  • Best (and Free!!) Resources to Understand Nuts and Bolts of Deep Learning

    ...iques) is here. I, however, used this quick tutorial to learn about them.   Some other good reviews/tutorials   A good tutorial about GANs (Generative Adversarial Networks) and generative models in general is what Goodfellow gave in ICLR 2016. It can be found here. Neural Networks have...

    https://www.kdnuggets.com/2018/07/best-free-resources-understand-nuts-bolts-deep-learning.html

  • Machine Learning & Artificial Intelligence: Main Developments in 2016 and Key Trends in 2017">Gold BlogMachine Learning & Artificial Intelligence: Main Developments in 2016 and Key Trends in 2017

    ...phaGo (DeepMind's network which beat the Go world champion using deep RL). Over the whole year we have seen a series of papers showing the success of generative adversarial networks (for unsupervised learning of generative models). Also in the area of unsupervised learning, we have seen the...

    https://www.kdnuggets.com/2016/12/machine-learning-artificial-intelligence-main-developments-2016-key-trends-2017.html

  • Medical Image Analysis with Deep Learning 

    ...up. He works with research, technology and business leaders to derive insights from data. Original. Reposted with permission. Related: Deep Learning, Generative Adversarial Networks & Boxing – Toward a Fundamental Understanding I’m a data scientist – mind if I do surgery on your heart? arXiv Paper...

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  • Another 10 Free Must-See Courses for Machine Learning and Data Science">Platinum BlogAnother 10 Free Must-See Courses for Machine Learning and Data Science

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