Measuring dataset similarity using optimal transport
https://www.microsoft.com/en-us/research/blog/measuring-dataset-similarity-using-optimal-transport/
https://www.microsoft.com/en-us/research/blog/measuring-dataset-similarity-using-optimal-transport/
Microsoft Research
Measuring dataset similarity using optimal transport - Microsoft Research
Is FashionMNIST, a dataset of images of clothing items labeled by category, more similar to MNIST or to USPS, both of which are classification datasets of handwritten digits? This is a pretty hard question to answer, but the solution could have an impact…
🎞 Robust and efficient post-processing for video object detection
REPP is a learning based post-processing method to improve video object detections from any object detector.
Github: https://github.com/AlbertoSabater/Robust-and-efficient-post-processing-for-video-object-detection
Paper: https://arxiv.org/abs/2009.11050
REPP is a learning based post-processing method to improve video object detections from any object detector.
Github: https://github.com/AlbertoSabater/Robust-and-efficient-post-processing-for-video-object-detection
Paper: https://arxiv.org/abs/2009.11050
Introduction to Time Series Analysis in Python
https://www.kdnuggets.com/2020/09/introduction-time-series-analysis-python.html
https://www.kdnuggets.com/2020/09/introduction-time-series-analysis-python.html
KDnuggets
Introduction to Time Series Analysis in Python - KDnuggets
Data that is updated in real-time requires additional handling and special care to prepare it for machine learning models. The important Python library, Pandas, can be used for most of this work, and this tutorial guides you through this process for analyzing…
45+ источников о data science: подборка телеграм-каналов, блогов и СМИ
https://embedika.ru/blog/resursyi-o-data-science
https://embedika.ru/blog/resursyi-o-data-science
Embedika
46 ресурсов о data science: блоги, telegram-каналы и СМИ | Embedika
Подборка проверенных источников о data science: блоги, телеграм-каналы, twitter, СМИ. Для специалистов и всех тех, кто хочет разобраться, как устроена наука о данных
Retrieval Augmented Generation: Streamlining the creation of intelligent natural language processing models
https://ai.facebook.com/blog/retrieval-augmented-generation-streamlining-the-creation-of-intelligent-natural-language-processing-models
https://ai.facebook.com/blog/retrieval-augmented-generation-streamlining-the-creation-of-intelligent-natural-language-processing-models
Meta
Retrieval Augmented Generation: Streamlining the creation of intelligent natural language processing models
Teaching computers to understand how humans write and speak, known as natural language processing or NLP, is one of the oldest challenges in AI research. There has been…
Дата-сайентисты, участвуйте в онлайн-хакатоне и поборитесь за призовой фонд в 10 000 000 рублей!
Нестандартные задачи, участие из любой точки РФ - все это хакатон “Лидеры цифровой трансформации”!
Собери команду, выбери задачу и до встречи на хакатоне!
Подать заявку: https://clck.ru/R87EZ
Нестандартные задачи, участие из любой точки РФ - все это хакатон “Лидеры цифровой трансформации”!
Собери команду, выбери задачу и до встречи на хакатоне!
Подать заявку: https://clck.ru/R87EZ
PyTorch utilized in aim to accelerate drug discovery
https://ai.facebook.com/blog/pytorch-utilized-in-aim-to-accelerate-drug-discovery/
Speeding up drug discovery with advanced machine learning: https://medium.com/pytorch/speeding-up-drug-discovery-with-advanced-machine-learning-b17d59e0daa6
https://ai.facebook.com/blog/pytorch-utilized-in-aim-to-accelerate-drug-discovery/
Speeding up drug discovery with advanced machine learning: https://medium.com/pytorch/speeding-up-drug-discovery-with-advanced-machine-learning-b17d59e0daa6
Facebook
PyTorch utilized in aim to accelerate drug discovery
PyTorch helps AstraZeneca apply advanced machine learning to drug discovery.
Developing Real-Time, Automatic Sign Language Detection for Video Conferencing
https://ai.googleblog.com/2020/10/developing-real-time-automatic-sign.html
https://ai.googleblog.com/2020/10/developing-real-time-automatic-sign.html
research.google
Developing Real-Time, Automatic Sign Language Detection for Video Conferencing
Posted by Amit Moryossef, Research Intern, Google Research Video conferencing should be accessible to everyone, including users who communicate usi...
Fluence
Fluence is a Pytorch based deep learning library focussed on providing computationally efficient, low resource methods and algorithms for NLP.
https://github.com/prajjwal1/fluence
Fluence is a Pytorch based deep learning library focussed on providing computationally efficient, low resource methods and algorithms for NLP.
https://github.com/prajjwal1/fluence
GitHub
GitHub - prajjwal1/fluence: A deep learning library based on Pytorch focussed on low resource language research and robustness
A deep learning library based on Pytorch focussed on low resource language research and robustness - GitHub - prajjwal1/fluence: A deep learning library based on Pytorch focussed on low resource la...
A Strong Single-Stage Baseline for Long-Tailed Problems
Github: https://github.com/KaihuaTang/Long-Tailed-Recognition.pytorch
Paper: https://arxiv.org/abs/2009.12991
Github: https://github.com/KaihuaTang/Long-Tailed-Recognition.pytorch
Paper: https://arxiv.org/abs/2009.12991
iTorch is a teaching library for machine learning engineers who wish to learn about the internal concepts underlying deep learning systems.
https://minitorch.github.io/index.html
Github: https://github.com/minitorch/minitorch.github.io
https://minitorch.github.io/index.html
Github: https://github.com/minitorch/minitorch.github.io
Forwarded from TensorFlow
How TensorFlow docs uses Jupyter notebooks
https://blog.tensorflow.org/2020/10/how-tensorflow-docs-uses-juypter-notebooks.html
@tensorflowblog
https://blog.tensorflow.org/2020/10/how-tensorflow-docs-uses-juypter-notebooks.html
@tensorflowblog
blog.tensorflow.org
How TensorFlow docs uses Jupyter notebooks
Learn how tensorflow.org uses Jupyter notebooks, Google Colab, and other tools for interactive, testable documentation.
KiU-Net-pytorch
Github: https://github.com/jeya-maria-jose/KiU-Net-pytorch
Project: https://sites.google.com/view/kiunet/home
Paper: https://arxiv.org/abs/2006.04878
@ArtificialIntelligencedl
Github: https://github.com/jeya-maria-jose/KiU-Net-pytorch
Project: https://sites.google.com/view/kiunet/home
Paper: https://arxiv.org/abs/2006.04878
@ArtificialIntelligencedl
Research highlights: Robustness of Bayesian Neural Networks to Gradient-Based Attacks (2020)
https://statsandai.wordpress.com/2020/10/08/research-highlights-robustness-of-bayesian-neural-networks-to-gradient-based-attacks/
https://statsandai.wordpress.com/2020/10/08/research-highlights-robustness-of-bayesian-neural-networks-to-gradient-based-attacks/
Stats & AI
Research highlights: Robustness of Bayesian Neural Networks to Gradient-Based Attacks, by Carbone et al (2020)
Introduction A more fun example than the gibbon, from Athalye et al ‘Synthesizing Robust Adversarial Examples’ 2018 Deep learning’s vulnerability to adversarial attacks has become…
Clarifying exceptions and visualizing tensor operations in deep learning code.
https://explained.ai/tensor-sensor/index.html
https://explained.ai/tensor-sensor/index.html
Understanding self-supervised and contrastive learning with "Bootstrap Your Own Latent" (BYOL)
https://untitled-ai.github.io/understanding-self-supervised-contrastive-learning.html
https://untitled-ai.github.io/understanding-self-supervised-contrastive-learning.html