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Restricting the Flow: Information Bottlenecks for Attribution
https://arxiv.org/abs/2001.00396v1
Code: https://github.com/attribution-bottleneck/attribution-bottleneck-pytorch
https://arxiv.org/abs/2001.00396v1
Code: https://github.com/attribution-bottleneck/attribution-bottleneck-pytorch
Differentiable Architecture Search
https://github.com/quark0/darts
RobustDARTS: https://github.com/MetaAnonym/RobustDARTS
Paper : https://openreview.net/forum?id=H1gDNyrKDS
https://github.com/quark0/darts
RobustDARTS: https://github.com/MetaAnonym/RobustDARTS
Paper : https://openreview.net/forum?id=H1gDNyrKDS
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Pytorch implementation for few-shot photorealistic video-to-video translation.
https://github.com/NVlabs/few-shot-vid2vid
Few-shot Video-to-Video Synthesis
https://nvlabs.github.io/few-shot-vid2vid/
Paper : https://arxiv.org/abs/1910.12713
@ai_machinelearning_big_data
https://github.com/NVlabs/few-shot-vid2vid
Few-shot Video-to-Video Synthesis
https://nvlabs.github.io/few-shot-vid2vid/
Paper : https://arxiv.org/abs/1910.12713
@ai_machinelearning_big_data
Ecovacs Robotics: the AI robotic vacuum cleaner powered by TensorFlow
https://blog.tensorflow.org/2020/01/ecovacs-robotics-ai-robotic-vacuum.html
https://blog.tensorflow.org/2020/01/ecovacs-robotics-ai-robotic-vacuum.html
blog.tensorflow.org
Ecovacs Robotics: the AI robotic vacuum cleaner powered by TensorFlow
The TensorFlow blog contains regular news from the TensorFlow team and the community, with articles on Python, TensorFlow.js, TF Lite, TFX, and more.
MuZero: DeepMind’s New AI Mastered More Than 50 Games
https://www.youtube.com/watch?v=hYV4-m7_SK8
Paper: https://arxiv.org/abs/1911.08265
Github: https://github.com/johan-gras/MuZer
Example: https://github.com/YuriCat/MuZeroJupyterExample
A simple implementation of MuZero algorithm for connect4 game
https://github.com/Zeta36/muzero
https://www.youtube.com/watch?v=hYV4-m7_SK8
Paper: https://arxiv.org/abs/1911.08265
Github: https://github.com/johan-gras/MuZer
Example: https://github.com/YuriCat/MuZeroJupyterExample
A simple implementation of MuZero algorithm for connect4 game
https://github.com/Zeta36/muzero
YouTube
MuZero: DeepMind’s New AI Mastered More Than 50 Games
❤️ Check out Linode here and get $20 free credit on your account: https://www.linode.com/papers
📝 The paper "Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model" is available here:
https://arxiv.org/abs/1911.08265
🙏 We would like to thank…
📝 The paper "Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model" is available here:
https://arxiv.org/abs/1911.08265
🙏 We would like to thank…
From Open Set to Closed Set: Supervised Spatial Divide-and-Conquer for Object Counting
https://github.com/xhp-hust-2018-2011/S-DCNet
https://github.com/xhp-hust-2018-2011/SS-DCNet
Paper https://arxiv.org/abs/2001.01886v1
https://github.com/xhp-hust-2018-2011/S-DCNet
https://github.com/xhp-hust-2018-2011/SS-DCNet
Paper https://arxiv.org/abs/2001.01886v1
GitHub
GitHub - xhp-hust-2018-2011/S-DCNet: Implementaion of S-DCNet (ICCV 2019)
Implementaion of S-DCNet (ICCV 2019). Contribute to xhp-hust-2018-2011/S-DCNet development by creating an account on GitHub.
Google Research: Looking Back at 2019, and Forward to 2020 and Beyond
https://ai.googleblog.com/2020/01/google-research-looking-back-at-2019.html
https://ai.googleblog.com/2020/01/google-research-looking-back-at-2019.html
research.google
Google Research: Looking Back at 2019, and Forward to 2020 and Beyond
Posted by Jeff Dean, Senior Fellow and SVP of Google Research and Health, on behalf of the entire Google Research community The goal of Google Re...
Non-local Neural Networks
Detectron is Facebook AI Research's software system that implements state-of-the-art object detection algorithms, including Mask R-CNN
https://github.com/facebookresearch/detectron
Non-local Neural Networks for Video Classification:https://github.com/facebookresearch/video-nonlocal-net
Paper: https://arxiv.org/abs/1711.07971v3
PySlowFast
https://github.com/facebookresearch/SlowFast
Detectron is Facebook AI Research's software system that implements state-of-the-art object detection algorithms, including Mask R-CNN
https://github.com/facebookresearch/detectron
Non-local Neural Networks for Video Classification:https://github.com/facebookresearch/video-nonlocal-net
Paper: https://arxiv.org/abs/1711.07971v3
PySlowFast
https://github.com/facebookresearch/SlowFast
A Gentle Introduction to Probability Metrics for Imbalanced Classification
https://machinelearningmastery.com/probability-metrics-for-imbalanced-classification/
https://machinelearningmastery.com/probability-metrics-for-imbalanced-classification/
MachineLearningMastery.com
A Gentle Introduction to Probability Metrics for Imbalanced Classification - MachineLearningMastery.com
Classification predictive modeling involves predicting a class label for examples, although some problems require the prediction of a probability of class membership. For these problems, the crisp class labels are not required, and instead, the likelihood…
👨🦱 DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detection
Code: https://github.com/EndlessSora/DeeperForensics-1.0
Paper: https://arxiv.org/abs/2001.03024v1
Code: https://github.com/EndlessSora/DeeperForensics-1.0
Paper: https://arxiv.org/abs/2001.03024v1
🚶 HybridPose: 6D Object Pose Estimation under Hybrid Representations
https://github.com/chensong1995/HybridPose
Paper: https://arxiv.org/abs/2001.01869
Pixel-wise Voting Network for 6DoF Pose Estimation: https://github.com/zju3dv/pvnet
https://github.com/chensong1995/HybridPose
Paper: https://arxiv.org/abs/2001.01869
Pixel-wise Voting Network for 6DoF Pose Estimation: https://github.com/zju3dv/pvnet
Transformers-For-Negation-and-Speculation
https://www.depends-on-the-definition.com/named-entity-recognition-with-bert/
State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch:
https://github.com/huggingface/transformers
Code: https://github.com/adityak6798/Transformers-For-Negation-and-Speculation
NegBERT: A Transfer Learning Approach for Negation Detection and Scope Resolution: https://arxiv.org/abs/1911.04211
Resolving the Scope of Speculation and Negation using Transformer-Based Architectures:
https://arxiv.org/abs/2001.02885
https://www.depends-on-the-definition.com/named-entity-recognition-with-bert/
State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch:
https://github.com/huggingface/transformers
Code: https://github.com/adityak6798/Transformers-For-Negation-and-Speculation
NegBERT: A Transfer Learning Approach for Negation Detection and Scope Resolution: https://arxiv.org/abs/1911.04211
Resolving the Scope of Speculation and Negation using Transformer-Based Architectures:
https://arxiv.org/abs/2001.02885
GitHub
GitHub - huggingface/transformers: 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models…
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - GitHub - huggingface/t...
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.