AdaBelief Optimizer: fast as Adam, generalizes as good as SGD, and sufficiently stable to train GANs.
https://juntang-zhuang.github.io/adabelief/
Github: https://github.com/juntang-zhuang/Adabelief-Optimizer#a-quick-look-at-the-algorithm
Paper: https://arxiv.org/abs/2010.07468v1
https://juntang-zhuang.github.io/adabelief/
Github: https://github.com/juntang-zhuang/Adabelief-Optimizer#a-quick-look-at-the-algorithm
Paper: https://arxiv.org/abs/2010.07468v1
juntang-zhuang.github.io
AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients
Crack the top 40 machine learning interview questions
https://levelup.gitconnected.com/crack-the-top-40-machine-learning-interview-questions-a7526335bcdc
https://levelup.gitconnected.com/crack-the-top-40-machine-learning-interview-questions-a7526335bcdc
Medium
Crack the top 40 machine learning interview questions
Today, take a deep dive into the top 40 machine learning interview questions for any FAANG company.
Contrastive Learning with Hard Negative Samples
Github: https://github.com/joshr17/HCL
Paper: https://arxiv.org/pdf/2010.04592.pdf
Github: https://github.com/joshr17/HCL
Paper: https://arxiv.org/pdf/2010.04592.pdf
Containerized end-to-end analytics of Spotify data using Python
https://pythonawesome.com/containerized-end-to-end-analytics-of-spotify-data-using-python/
https://pythonawesome.com/containerized-end-to-end-analytics-of-spotify-data-using-python/
Announcing the NVIDIA NVTabular Open Beta with Multi-GPU Support and New Data Loaders
https://developer.nvidia.com/blog/announcing-the-nvtabular-open-beta-with-multi-gpu-support-and-new-data-loaders/
https://developer.nvidia.com/blog/announcing-the-nvtabular-open-beta-with-multi-gpu-support-and-new-data-loaders/
Forwarded from TensorFlow
Rethinking Attention with Performers
https://ai.googleblog.com/2020/10/rethinking-attention-with-performers.html
@tensorflowblog
https://ai.googleblog.com/2020/10/rethinking-attention-with-performers.html
@tensorflowblog
research.google
Rethinking Attention with Performers
Posted by Krzysztof Choromanski and Lucy Colwell, Research Scientists, Google Research Transformer models have achieved state-of-the-art results ac...
FaceShifter — Unofficial PyTorch Implementation
Github: https://github.com/mindslab-ai/faceshifter
Paper: https://arxiv.org/abs/1912.13457
Github: https://github.com/mindslab-ai/faceshifter
Paper: https://arxiv.org/abs/1912.13457
Multilingual T5 (mT5) is a massively multilingual pretrained text-to-text transformer model
Github: https://github.com/google-research/multilingual-t5
Paper: https://arxiv.org/abs/2010.11934v1
Github: https://github.com/google-research/multilingual-t5
Paper: https://arxiv.org/abs/2010.11934v1
GitHub
GitHub - google-research/multilingual-t5
Contribute to google-research/multilingual-t5 development by creating an account on GitHub.
Contrastive learning of general purpose audio representations
https://github.com/google-research/google-research/tree/master/cola
https://github.com/google-research/google-research/tree/master/cola
Bitcoin Trading is Irrational! An Analysis of the Disposition Effect in Bitcoin.
Github: https://github.com/jschatzmann/CryptoDisposition
Paper: https://arxiv.org/abs/2010.12415v1
Github: https://github.com/jschatzmann/CryptoDisposition
Paper: https://arxiv.org/abs/2010.12415v1
Trajectory-wise Multiple Choice Learning for Generalization in Reinforcement Learning
https://github.com/younggyoseo/trajectory_mcl
https://github.com/younggyoseo/trajectory_mcl
Easy-to-interpret neurons may hinder learning in deep neural networks
https://ai.facebook.com/blog/easy-to-interpret-neurons-may-hinder-learning-in-deep-neural-networks/
https://ai.facebook.com/blog/easy-to-interpret-neurons-may-hinder-learning-in-deep-neural-networks/
Facebook
Easy-to-interpret neurons may hinder learning in deep neural networks
What does an AI model “understand” and why? A long-held belief is there are easy-to-interpret neurons -- or “class selective” neurons. For instance, finding neurons that
Abdominal Organ Segmentation A Solved Problem?
Github: https://github.com/MIC-DKFZ/nnunet
Paper: https://arxiv.org/abs/2010.14808v1
@ArtificialIntelligencedl
Github: https://github.com/MIC-DKFZ/nnunet
Paper: https://arxiv.org/abs/2010.14808v1
@ArtificialIntelligencedl
GitHub
GitHub - MIC-DKFZ/nnUNet
Contribute to MIC-DKFZ/nnUNet development by creating an account on GitHub.
Building Neural Networks with PyTorch in Google Colab
https://www.kdnuggets.com/2020/10/building-neural-networks-pytorch-google-colab.html
@ArtificialIntelligencedl
https://www.kdnuggets.com/2020/10/building-neural-networks-pytorch-google-colab.html
@ArtificialIntelligencedl
Random Forest for Time Series Forecasting
https://machinelearningmastery.com/random-forest-for-time-series-forecasting/
@ArtificialIntelligencedl
https://machinelearningmastery.com/random-forest-for-time-series-forecasting/
@ArtificialIntelligencedl
Experimental design for MRI by greedy policy search
Github: https://github.com/Timsey/pg_mri
Paper: https://arxiv.org/abs/2010.16262v1
@ArtificialIntelligencedl
Github: https://github.com/Timsey/pg_mri
Paper: https://arxiv.org/abs/2010.16262v1
@ArtificialIntelligencedl
Bridging Visual Representations’ Decoder Integrates CV Object Detection Frameworks
https://syncedreview.com/2020/11/02/bridging-visual-representations-decoder-integrates-cv-object-detection-frameworks/
@ArtificialIntelligencedl
https://syncedreview.com/2020/11/02/bridging-visual-representations-decoder-integrates-cv-object-detection-frameworks/
@ArtificialIntelligencedl
Synced | AI Technology & Industry Review
‘Bridging Visual Representations’ Decoder Integrates CV Object Detection Frameworks | Synced
NeurIPS 2020 Institute of Automation CAS and Microsoft Research Asia paper presents an attention-based decoder that integrates CV object representations