Optuna: A hyperparameter optimization framework
Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning.
Code: https://github.com/optuna/optuna
Paper: https://arxiv.org/abs/1907.10902v1
Tutorial: https://optuna.org/
Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning.
Code: https://github.com/optuna/optuna
Paper: https://arxiv.org/abs/1907.10902v1
Tutorial: https://optuna.org/
GitHub
GitHub - optuna/optuna: A hyperparameter optimization framework
A hyperparameter optimization framework. Contribute to optuna/optuna development by creating an account on GitHub.
Neural Arithmetic Units
Code for Neural Arithmetic Units (ICLR) and Measuring Arithmetic Extrapolation Performance (SEDL|NeurIPS):
https://github.com/AndreasMadsen/stable-nalu
Paper : https://openreview.net/forum?id=H1gNOeHKPS
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Code for Neural Arithmetic Units (ICLR) and Measuring Arithmetic Extrapolation Performance (SEDL|NeurIPS):
https://github.com/AndreasMadsen/stable-nalu
Paper : https://openreview.net/forum?id=H1gNOeHKPS
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Plato Dialogue System: A Flexible Conversational AI Research Platform
Code: https://github.com/uber-research/plato-research-dialogue-system
Introducing the Plato Research : https://eng.uber.com/plato-research-dialogue-system/
Paper: https://arxiv.org/abs/2001.06463v1
Code: https://github.com/uber-research/plato-research-dialogue-system
Introducing the Plato Research : https://eng.uber.com/plato-research-dialogue-system/
Paper: https://arxiv.org/abs/2001.06463v1
AI Habitat state-of-the-art simulation platform adds object interactivity
A major update to Facebook AI’s open source AI Habitat platform , which enables significantly faster training of embodied AI agents in a variety of photorealistic 3D virtual environments.
https://ai.facebook.com/blog/ai-habitat-state-of-the-art-simulation-platform-adds-object-interactivity/
Github: https://github.com/facebookresearch/habitat-sim/
https://github.com/facebookresearch/habitat-api
Paper: Are We Making Real Progress in Simulated Environments? Measuring the Sim2Real Gap in Embodied Visual Navigation
https://arxiv.org/abs/1912.06321
A major update to Facebook AI’s open source AI Habitat platform , which enables significantly faster training of embodied AI agents in a variety of photorealistic 3D virtual environments.
https://ai.facebook.com/blog/ai-habitat-state-of-the-art-simulation-platform-adds-object-interactivity/
Github: https://github.com/facebookresearch/habitat-sim/
https://github.com/facebookresearch/habitat-api
Paper: Are We Making Real Progress in Simulated Environments? Measuring the Sim2Real Gap in Embodied Visual Navigation
https://arxiv.org/abs/1912.06321
Facebook
AI Habitat simulation platform adds object interactivity
We’re releasing a major update to Facebook AI’s open source AI Habitat platform for training embodied AI agents in photorealistic 3D virtual environments. AI Habitat now supports interactive objects, realistic physics modeling, and more.
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🧠 Releasing the Drosophila Hemibrain Connectome — The Largest Synapse-Resolution Map of Brain Connectivity
https://ai.googleblog.com/2020/01/releasing-drosophila-hemibrain.html
https://ai.googleblog.com/2020/01/releasing-drosophila-hemibrain.html
GL2vec: Graph Embedding Enriched by Line Graphs with Edge Features
Code: https://github.com/benedekrozemberczki/karateclub
Paper: https://link.springer.com/chapter/10.1007/978-3-030-36718-3_1
https://karateclub.readthedocs.io
Code: https://github.com/benedekrozemberczki/karateclub
Paper: https://link.springer.com/chapter/10.1007/978-3-030-36718-3_1
https://karateclub.readthedocs.io
GitHub
GitHub - benedekrozemberczki/karateclub: Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on…
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020) - benedekrozemberczki/karateclub
🚀 Google just published 25 million free datasets
https://towardsdatascience.com/google-just-published-25-million-free-datasets-d83940e24284
Datasetsearch: https://datasetsearch.research.google.com
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https://towardsdatascience.com/google-just-published-25-million-free-datasets-d83940e24284
Datasetsearch: https://datasetsearch.research.google.com
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Medium
Google just published 25 million free datasets
Here’s what you need to know about the largest data repository in the world
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
Code: https://github.com/google-research/fixmatch
Paper: https://arxiv.org/abs/2001.07685
Code: https://github.com/google-research/fixmatch
Paper: https://arxiv.org/abs/2001.07685
GitHub
GitHub - google-research/fixmatch: A simple method to perform semi-supervised learning with limited data.
A simple method to perform semi-supervised learning with limited data. - google-research/fixmatch
Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation
https://vllab.ucmerced.edu/ym41608/projects/CrossDomainFewShot/
Code and data: https://github.com/hytseng0509/CrossDomainFewShot
Paper: https://arxiv.org/abs/2001.08735
https://vllab.ucmerced.edu/ym41608/projects/CrossDomainFewShot/
Code and data: https://github.com/hytseng0509/CrossDomainFewShot
Paper: https://arxiv.org/abs/2001.08735
Channel Pruning via Automatic Structure Search
Code: https://github.com/lmbxmu/ABCPruner
Paper: https://arxiv.org/abs/2001.08565
Code: https://github.com/lmbxmu/ABCPruner
Paper: https://arxiv.org/abs/2001.08565
Multi-task self-supervised learning for Robust Speech Recognition
A PASE model can be used as a speech feature extractor or to pre-train an encoder for our desired end-task
Code: https://github.com/santi-pdp/pase
Paper: https://arxiv.org/abs/2001.09239v1
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A PASE model can be used as a speech feature extractor or to pre-train an encoder for our desired end-task
Code: https://github.com/santi-pdp/pase
Paper: https://arxiv.org/abs/2001.09239v1
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Hyperparameter tuning with Keras Tuner
https://blog.tensorflow.org/2020/01/hyperparameter-tuning-with-keras-tuner.html
Github: https://github.com/keras-team/keras-tuner
Distributed Tuning: https://keras-team.github.io/keras-tuner/tutorials/distributed-tuning/
https://blog.tensorflow.org/2020/01/hyperparameter-tuning-with-keras-tuner.html
Github: https://github.com/keras-team/keras-tuner
Distributed Tuning: https://keras-team.github.io/keras-tuner/tutorials/distributed-tuning/
blog.tensorflow.org
Hyperparameter tuning with Keras Tuner
The TensorFlow blog contains regular news from the TensorFlow team and the community, with articles on Python, TensorFlow.js, TF Lite, TFX, and more.
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f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation
Code: https://github.com/saic-vul/fbrs_interactive_segmentation
Paper: https://arxiv.org/abs/2001.10331
Code: https://github.com/saic-vul/fbrs_interactive_segmentation
Paper: https://arxiv.org/abs/2001.10331
Uplift modeling tutorial
https://habr.com/ru/company/ru_mts/blog/485980/
Code example: https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/RetailHero.ipynb
https://habr.com/ru/company/ru_mts/blog/485980/
Code example: https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/RetailHero.ipynb
Хабр
Туториал по uplift моделированию. Часть 1
Команда Big Data МТС активно извлекает знания из имеющихся данных и решает большое количество задач для бизнеса. Один из типов задач машинного обучения, с которыми мы сталкиваемся – это задачи...
TVR: A Large-Scale Dataset for Video-Subtitle Moment Retrieval
Github: https://github.com/jayleicn/TVRetrieval
PyTorch implementation of MultiModal Transformer (MMT), a method for multimodal (video + subtitle) captioning: https://github.com/jayleicn/TVCaption
Paper: https://arxiv.org/abs/2001.09099v1
Github: https://github.com/jayleicn/TVRetrieval
PyTorch implementation of MultiModal Transformer (MMT), a method for multimodal (video + subtitle) captioning: https://github.com/jayleicn/TVCaption
Paper: https://arxiv.org/abs/2001.09099v1
Statistical_Consequences_of_Fat.pdf
27.3 MB
📚Fresh book by Nassim Taleb
Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications
https://arxiv.org/abs/2001.10488
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Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications
https://arxiv.org/abs/2001.10488
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Open Source Differentiable Computer Vision Library for PyTorch
https://kornia.org
Code: https://github.com/kornia/kornia
Paper: https://arxiv.org/abs/1910.02190v2
https://kornia.org
Code: https://github.com/kornia/kornia
Paper: https://arxiv.org/abs/1910.02190v2
Project DeepSpeech
A TensorFlow implementation of Baidu's DeepSpeech architecture
Code: https://github.com/mozilla/DeepSpeech
Tensorflow & Pytorch: https://github.com/DemisEom/SpecAugment
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition:
https://arxiv.org/pdf/1904.08779.pdf
A TensorFlow implementation of Baidu's DeepSpeech architecture
Code: https://github.com/mozilla/DeepSpeech
Tensorflow & Pytorch: https://github.com/DemisEom/SpecAugment
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition:
https://arxiv.org/pdf/1904.08779.pdf
GitHub
GitHub - mozilla/DeepSpeech: DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in…
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers. - mozilla/DeepSpeech
Filter Sketch for Network Pruning
Framework of FilterSketch. The top displays the second-order covariance of the pre-trained CNN
Code: https://github.com/lmbxmu/FilterSketch
Paper: https://arxiv.org/abs/2001.08514v1
Framework of FilterSketch. The top displays the second-order covariance of the pre-trained CNN
Code: https://github.com/lmbxmu/FilterSketch
Paper: https://arxiv.org/abs/2001.08514v1