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Implementation of the BASIS algorithm for source separation with deep generative priors
This repository provides an implementation of the BASIS (Bayesian Annealed SIgnal Source) separation algorithm. BASIS separation uses annealed Langevin dynamics to sample from the posterior distribution of source components given a mixed signal.
Github: https://github.com/jthickstun/basis-separation
Paper: https://arxiv.org/abs/2002.07942
This repository provides an implementation of the BASIS (Bayesian Annealed SIgnal Source) separation algorithm. BASIS separation uses annealed Langevin dynamics to sample from the posterior distribution of source components given a mixed signal.
Github: https://github.com/jthickstun/basis-separation
Paper: https://arxiv.org/abs/2002.07942
A Gentle Introduction to the Fbeta-Measure for Machine Learning
https://machinelearningmastery.com/fbeta-measure-for-machine-learning/
https://machinelearningmastery.com/fbeta-measure-for-machine-learning/
JAX-based neural network library
https://github.com/deepmind/dm-haiku
Haiku Documentation: https://dm-haiku.readthedocs.io/en/latest/
https://github.com/deepmind/dm-haiku
Haiku Documentation: https://dm-haiku.readthedocs.io/en/latest/
GitHub
GitHub - google-deepmind/dm-haiku: JAX-based neural network library
JAX-based neural network library. Contribute to google-deepmind/dm-haiku development by creating an account on GitHub.
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Exploring Transfer Learning with T5: the Text-To-Text Transfer Transformer
https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html
Code: https://colab.research.google.com/github/google-research/text-to-text-transfer-transformer/blob/master/notebooks/t5-trivia.ipynb
Github: https://github.com/google-research/text-to-text-transfer-transformer
https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html
Code: https://colab.research.google.com/github/google-research/text-to-text-transfer-transformer/blob/master/notebooks/t5-trivia.ipynb
Github: https://github.com/google-research/text-to-text-transfer-transformer
How to Calibrate Probabilities for Imbalanced Classification
https://machinelearningmastery.com/probability-calibration-for-imbalanced-classification/
https://machinelearningmastery.com/probability-calibration-for-imbalanced-classification/
ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network
AdelaiDet is an open source toolbox for multiple instance-level detection applications.
Code: https://github.com/aim-uofa/adet
Paper: https://arxiv.org/pdf/2002.10200v1.pdf
AdelaiDet is an open source toolbox for multiple instance-level detection applications.
Code: https://github.com/aim-uofa/adet
Paper: https://arxiv.org/pdf/2002.10200v1.pdf
❤1
Open Images V6 — Now Featuring Localized Narratives
Open Images is the largest annotated image dataset in many regards, for use in training the latest deep convolutional neural networks for computer vision tasks
https://ai.googleblog.com/2020/02/open-images-v6-now-featuring-localized.html
Open Images Dataset V6 + Extensions: https://storage.googleapis.com/openimages/web/index.html
Localized Narratives Example: https://www.youtube.com/watch?v=mZqHVUstmIQ&feature=emb_logo
Open Images is the largest annotated image dataset in many regards, for use in training the latest deep convolutional neural networks for computer vision tasks
https://ai.googleblog.com/2020/02/open-images-v6-now-featuring-localized.html
Open Images Dataset V6 + Extensions: https://storage.googleapis.com/openimages/web/index.html
Localized Narratives Example: https://www.youtube.com/watch?v=mZqHVUstmIQ&feature=emb_logo
Using Reinforcement Learning in the Algorithmic Trading Problem
Trading with recurrent actor-critic reinforcement learning
Code: https://github.com/evgps/a3c_trading
Paper: https://arxiv.org/abs/2002.11523v1
Trading with recurrent actor-critic reinforcement learning
Code: https://github.com/evgps/a3c_trading
Paper: https://arxiv.org/abs/2002.11523v1
FreezeD: A Simple Baseline for Fine-tuning GANs
Simple Baseline for Fine-Tuning GANs
Code: https://github.com/sangwoomo/freezeD
Paper: https://arxiv.org/abs/2002.10964
Datasets: https://vcla.stat.ucla.edu/people/zhangzhang-si/HiT/exp5.html
Simple Baseline for Fine-Tuning GANs
Code: https://github.com/sangwoomo/freezeD
Paper: https://arxiv.org/abs/2002.10964
Datasets: https://vcla.stat.ucla.edu/people/zhangzhang-si/HiT/exp5.html
Imbalanced Classification Model to Detect Mammography Microcalcifications
https://machinelearningmastery.com/imbalanced-classification-model-to-detect-microcalcifications/
https://machinelearningmastery.com/imbalanced-classification-model-to-detect-microcalcifications/
MachineLearningMastery.com
Imbalanced Classification Model to Detect Mammography Microcalcifications - MachineLearningMastery.com
Cancer detection is a popular example of an imbalanced classification problem because there are often significantly more cases of non-cancer than actual cancer.
A standard imbalanced classification dataset is the mammography dataset that involves detecting…
A standard imbalanced classification dataset is the mammography dataset that involves detecting…
Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods
FlyingSquid is a new framework for automatically building models from multiple noisy label sources.
Code: https://github.com/HazyResearch/flyingsquid
Blog: https://hazyresearch.stanford.edu/flyingsquid
Paper: https://arxiv.org/abs/2002.11955v1
FlyingSquid is a new framework for automatically building models from multiple noisy label sources.
Code: https://github.com/HazyResearch/flyingsquid
Blog: https://hazyresearch.stanford.edu/flyingsquid
Paper: https://arxiv.org/abs/2002.11955v1
160+ Data Science Interview Questions
https://hackernoon.com/160-data-science-interview-questions-415s3y2a
https://hackernoon.com/160-data-science-interview-questions-415s3y2a
Hackernoon
160+ Data Science Interview Questions | HackerNoon
A typical interview process for a data science position includes multiple rounds. Often, one of such rounds covers theoretical concepts, where the goal is to determine if the candidate knows the fundamentals of machine learning.
Meta-Transfer Learning for Zero-Shot Super-Resolution
Code: https://github.com/JWSoh/MZSR
Paper: https://arxiv.org/abs/2002.12213v1
Code: https://github.com/JWSoh/MZSR
Paper: https://arxiv.org/abs/2002.12213v1
Better scalability with Cloud TPU pods and TensorFlow 2.1
https://cloud.google.com/blog/products/ai-machine-learning/better-scalability-with-cloud-tpu-pods-and-tensorflow-2-1
TensorFlow Official Models: https://github.com/tensorflow/models/tree/master/official
https://cloud.google.com/blog/products/ai-machine-learning/better-scalability-with-cloud-tpu-pods-and-tensorflow-2-1
TensorFlow Official Models: https://github.com/tensorflow/models/tree/master/official
Google Cloud Blog
Cloud TPU Pods generally available, now include TensorFlow 2.1 support | Google Cloud Blog
Cloud TPU Pods are now generally available, and include TensorFlow 2.1 support and other new features.
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Deep Image Spatial Transformation for Person Image Generation
Pose-guided person image generation is to transform a source person image to a target pose.
Github: https://github.com/RenYurui/Global-Flow-Local-Attention
Paper: https://arxiv.org/abs/2003.00696v1
Pose-guided person image generation is to transform a source person image to a target pose.
Github: https://github.com/RenYurui/Global-Flow-Local-Attention
Paper: https://arxiv.org/abs/2003.00696v1
Sign Language Recognition with Deep Learning and PyTorch
https://theaisummer.com/Sign-Language-Recognition-with-PyTorch/
https://theaisummer.com/Sign-Language-Recognition-with-PyTorch/
MARKOV CHAIN MONTE CARLO (MCMC) SAMPLING
https://www.tweag.io/posts/2019-10-25-mcmc-intro1.html
Habr ru: https://habr.com/ru/company/piter/blog/491268/
https://www.tweag.io/posts/2019-10-25-mcmc-intro1.html
Habr ru: https://habr.com/ru/company/piter/blog/491268/
A software toolkit for research on general-purpose text understanding models
jiant is a software toolkit for natural language processing research, designed to facilitate work on multitask learning and transfer learning for sentence understanding tasks
https://jiant.info/
Code: https://github.com/nyu-mll/jiant
Paper: https://arxiv.org/pdf/2003.02249v1.pdf
jiant is a software toolkit for natural language processing research, designed to facilitate work on multitask learning and transfer learning for sentence understanding tasks
https://jiant.info/
Code: https://github.com/nyu-mll/jiant
Paper: https://arxiv.org/pdf/2003.02249v1.pdf
GitHub
GitHub - nyu-mll/jiant: jiant is an nlp toolkit
jiant is an nlp toolkit. Contribute to nyu-mll/jiant development by creating an account on GitHub.
Simulating the Universe in TensorFlow
https://blog.tensorflow.org/2020/03/simulating-universe-in-tensorflow.html
https://blog.tensorflow.org/2020/03/simulating-universe-in-tensorflow.html