Using neural networks to solve advanced mathematics equations
https://ai.facebook.com/blog/using-neural-networks-to-solve-advanced-mathematics-equations/
https://ai.facebook.com/blog/using-neural-networks-to-solve-advanced-mathematics-equations/
Meta
Using neural networks to solve advanced mathematics equations
Facebook AI has developed the first neural network that uses symbolic reasoning to solve advanced mathematics problems.
Rethinking Generalization of Neural Models: A Named Entity Recognition Case Study
Paper: https://arxiv.org/abs/2001.03844v1
Code https://github.com/pfliu-nlp/Named-Entity-Recognition-NER-Papers
Paper: https://arxiv.org/abs/2001.03844v1
Code https://github.com/pfliu-nlp/Named-Entity-Recognition-NER-Papers
GitHub
GitHub - pfliu-nlp/Named-Entity-Recognition-NER-Papers: An elaborate and exhaustive paper list for Named Entity Recognition (NER)
An elaborate and exhaustive paper list for Named Entity Recognition (NER) - pfliu-nlp/Named-Entity-Recognition-NER-Papers
PyTorch 1.4 released, domain libraries updated
https://pytorch.org/blog/pytorch-1-dot-4-released-and-domain-libraries-updated/
Examples using model parallel training for reinforcement learning and with an LSTM: https://github.com/pytorch/examples/tree/master/distributed/rpc
https://pytorch.org/blog/pytorch-1-dot-4-released-and-domain-libraries-updated/
Examples using model parallel training for reinforcement learning and with an LSTM: https://github.com/pytorch/examples/tree/master/distributed/rpc
PyTorch
PyTorch 1.4 released, domain libraries updated
Today, we’re announcing the availability of PyTorch 1.4, along with updates to the PyTorch domain libraries. These releases build on top of the announcements from NeurIPS 2019, where we shared the availability of PyTorch Elastic, a new classification framework…
Deep Image Compression using Decoder Side Information
Code: https://github.com/ayziksha/DSIN
Paper: https://arxiv.org/abs/2001.04753v1
Code: https://github.com/ayziksha/DSIN
Paper: https://arxiv.org/abs/2001.04753v1
SMOTE Oversampling for Imbalanced Classification with Python
https://machinelearningmastery.com/smote-oversampling-for-imbalanced-classification/
https://machinelearningmastery.com/smote-oversampling-for-imbalanced-classification/
Trax — your path to advanced deep learning
Trax helps you understand and explore advanced deep learning.
https://github.com/google/trax
Paper Reformer: The Efficient Transformer: https://arxiv.org/abs/2001.04451v1
Trax helps you understand and explore advanced deep learning.
https://github.com/google/trax
Paper Reformer: The Efficient Transformer: https://arxiv.org/abs/2001.04451v1
GitHub
GitHub - google/trax: Trax — Deep Learning with Clear Code and Speed
Trax — Deep Learning with Clear Code and Speed. Contribute to google/trax development by creating an account on GitHub.
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
@ai_machinelearning_big_data
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
@ai_machinelearning_big_data
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.
This media is not supported in your browser
VIEW IN TELEGRAM
🧠 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
@ai_machinelearning_big_data
https://towardsdatascience.com/google-just-published-25-million-free-datasets-d83940e24284
Datasetsearch: https://datasetsearch.research.google.com
@ai_machinelearning_big_data
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
@ai_machinelearning_big_data
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
@ai_machinelearning_big_data
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.
This media is not supported in your browser
VIEW IN TELEGRAM
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