Fourier Features Let Networks Learn
High Frequency Functions in Low Dimensional Domains
https://people.eecs.berkeley.edu/~bmild/fourfeat/index.html
High Frequency Functions in Low Dimensional Domains
https://people.eecs.berkeley.edu/~bmild/fourfeat/index.html
Neural Manifold Ordinary Differential Equations
Article: https://arxiv.org/abs/2006.10254
Github: https://github.com/CUVL/Neural-Manifold-Ordinary-Differential-Equations
Article: https://arxiv.org/abs/2006.10254
Github: https://github.com/CUVL/Neural-Manifold-Ordinary-Differential-Equations
How to Avoid Data Leakage When Performing Data Preparation
https://machinelearningmastery.com/data-preparation-without-data-leakage/
https://machinelearningmastery.com/data-preparation-without-data-leakage/
MachineLearningMastery.com
How to Avoid Data Leakage When Performing Data Preparation - MachineLearningMastery.com
Data preparation is the process of transforming raw data into a form that is appropriate for modeling. A naive approach to preparing data applies the transform on the entire dataset before evaluating the performance of the model. This results in a problem…
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
Given a low-resolution input image, PULSE searches the outputs of a generative model for high-resolution images that are perceptually realistic and downscale correctly.
Github: https://github.com/adamian98/pulse
Paper: https://arxiv.org/abs/2003.03808v1
Given a low-resolution input image, PULSE searches the outputs of a generative model for high-resolution images that are perceptually realistic and downscale correctly.
Github: https://github.com/adamian98/pulse
Paper: https://arxiv.org/abs/2003.03808v1
Google & DeepMind Researchers Revamp ImageNet
https://syncedreview.com/2020/06/23/google-deepmind-researchers-revamp-imagenet/
ImageNet: https://arxiv.org/pdf/2006.07159.pdf
https://syncedreview.com/2020/06/23/google-deepmind-researchers-revamp-imagenet/
ImageNet: https://arxiv.org/pdf/2006.07159.pdf
Synced | AI Technology & Industry Review
Google & DeepMind Researchers Revamp ImageNet | Synced
Google Brain in Zürich and DeepMind London researchers believe one of the world's most popular image databases may need a makeover.
A state-of-the-art, self-supervised framework for video understanding
https://ai.facebook.com/blog/a-state-of-the-art-self-supervised-framework-for-video-understanding/
https://ai.facebook.com/blog/a-state-of-the-art-self-supervised-framework-for-video-understanding/
Facebook
A state-of-the-art, self-supervised framework for video understanding
Generalized Data Transformations give us a systematic way of robustly learning the relationship between audio and visual information in order to learn about the structure of the world.
Learning Semantically Enhanced Feature for Fine-Grained Image Classification
Gitgub: https://github.com/cswluo/SEF
Paper: https://arxiv.org/abs/2006.13457v1
Gitgub: https://github.com/cswluo/SEF
Paper: https://arxiv.org/abs/2006.13457v1
Building AI Trading Systems
Lessons learned building a profitable algorithmic trading system using Reinforcement Learning techniques.
https://dennybritz.com/blog/ai-trading/
Lessons learned building a profitable algorithmic trading system using Reinforcement Learning techniques.
https://dennybritz.com/blog/ai-trading/
Dennybritz
Building AI Trading Systems
Lessons learned building a profitable algorithmic trading system using Reinforcement Learning techniques.
Tensor Programs II: Neural Tangent Kernel for Any Architecture
which shows the tangent kernel of any randomly initialized neural network converges in the large width limit.
Github: https://github.com/thegregyang/NTK4A
Paper: https://arxiv.org/abs/2006.14548
which shows the tangent kernel of any randomly initialized neural network converges in the large width limit.
Github: https://github.com/thegregyang/NTK4A
Paper: https://arxiv.org/abs/2006.14548
8 Top Books on Data Cleaning and Feature Engineering
https://machinelearningmastery.com/books-on-data-cleaning-data-preparation-and-feature-engineering/
https://machinelearningmastery.com/books-on-data-cleaning-data-preparation-and-feature-engineering/
SmartReply for YouTube Creators
https://ai.googleblog.com/2020/07/smartreply-for-youtube-creators.html
https://ai.googleblog.com/2020/07/smartreply-for-youtube-creators.html
Googleblog
SmartReply for YouTube Creators
Announcing CUDA on Windows Subsystem for Linux 2
https://developer.nvidia.com/blog/announcing-cuda-on-windows-subsystem-for-linux-2/
https://developer.nvidia.com/blog/announcing-cuda-on-windows-subsystem-for-linux-2/
NVIDIA Technical Blog
Announcing CUDA on Windows Subsystem for Linux 2
In response to popular demand, Microsoft announced a new feature of the Windows Subsystem for Linux 2 (WSL 2)—GPU acceleration—at the Build conference in May 2020. This feature opens the gate for many…
Generating cooking recipes using TensorFlow and LSTM Recurrent Neural Network: A step-by-step guide
https://www.kdnuggets.com/2020/07/generating-cooking-recipes-using-tensorflow.html
https://www.kdnuggets.com/2020/07/generating-cooking-recipes-using-tensorflow.html
KDnuggets
Generating cooking recipes using TensorFlow and LSTM Recurrent Neural Network: A step-by-step guide
A character-level LSTM (Long short-term memory) RNN (Recurrent Neural Network) is trained on ~100k recipes dataset using TensorFlow. The model suggested the recipes "Cream Soda with Onions", "Puff Pastry Strawberry Soup", "Zucchini flavor Tea", and "Salmon…
How to Use Feature Extraction on Tabular Data for Machine Learning - Machine Learning Mastery
https://machinelearningmastery.com/feature-extraction-on-tabular-data/
https://machinelearningmastery.com/feature-extraction-on-tabular-data/
Constructing a 3D Face Mesh from Face Landmarks in Real-Time with TensorFlow.js and Plot.js
https://heartbeat.fritz.ai/constructing-a-3d-face-mesh-from-face-landmarks-in-real-time-with-tensorflow-js-and-plot-js-62b177abcf9f
https://heartbeat.fritz.ai/constructing-a-3d-face-mesh-from-face-landmarks-in-real-time-with-tensorflow-js-and-plot-js-62b177abcf9f
Medium
Constructing a 3D Face Mesh from Face Landmarks in Real-Time with TensorFlow.js and Plot.js
Face landmark recognition and plotting using TensorFlow.js and plotly 3D
Wavelet Networks: Scale Equivariant Learning From Raw Waveforms
Github: https://github.com/dwromero/wavelet_networks
Paper: https://arxiv.org/abs/2006.05259
Github: https://github.com/dwromero/wavelet_networks
Paper: https://arxiv.org/abs/2006.05259