Not All Memories are Created Equal: Learning to Expire
Github: https://github.com/lucidrains/learning-to-expire-pytorch
Paper: https://openreview.net/forum?id=ZVBtN6B_6i7
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Github: https://github.com/lucidrains/learning-to-expire-pytorch
Paper: https://openreview.net/forum?id=ZVBtN6B_6i7
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🦠 COVID-Affinity-Model
Github: https://github.com/AlexTS1980/COVID-Affinity-Model
Paper: https://www.medrxiv.org/content/10.1101/2020.12.29.20248987v1.full.pdf
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Github: https://github.com/AlexTS1980/COVID-Affinity-Model
Paper: https://www.medrxiv.org/content/10.1101/2020.12.29.20248987v1.full.pdf
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🚀 DALL·E is a 12-billion parameter version of GPT-3 trained to generate images from text denoscriptions
Introduction: https://openai.com/blog/tags/multimodal/
Deepmind Blog: https://openai.com/blog/dall-e/
Github: https://github.com/openai/CLIP
Paper: https://cdn.openai.com/papers/Learning_Transferable_Visual_Models_From_Natural_Language.pdf
Colab: https://colab.research.google.com/github/openai/clip/blob/master/Interacting_with_CLIP.ipynb
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Introduction: https://openai.com/blog/tags/multimodal/
Deepmind Blog: https://openai.com/blog/dall-e/
Github: https://github.com/openai/CLIP
Paper: https://cdn.openai.com/papers/Learning_Transferable_Visual_Models_From_Natural_Language.pdf
Colab: https://colab.research.google.com/github/openai/clip/blob/master/Interacting_with_CLIP.ipynb
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🦾 Volumetric Grasping Network.
Github: https://github.com/ethz-asl/vgn
Paper: https://arxiv.org/abs/2101.01132
Video: https://www.youtube.com/watch?v=FXjvFDcV6E0&feature=youtu.be
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Github: https://github.com/ethz-asl/vgn
Paper: https://arxiv.org/abs/2101.01132
Video: https://www.youtube.com/watch?v=FXjvFDcV6E0&feature=youtu.be
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🔇 Deep Noise Suppression Challenge – ICASSP 2021
Github: https://github.com/microsoft/DNS-Challenge
Paper: https://arxiv.org/abs/2101.01902v1
Training and test datasets: https://github.com/microsoft/DNS-Challenge/tree/master/datasets
Challenge: https://www.microsoft.com/en-us/research/academic-program/deep-noise-suppression-challenge-icassp-2021/
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Github: https://github.com/microsoft/DNS-Challenge
Paper: https://arxiv.org/abs/2101.01902v1
Training and test datasets: https://github.com/microsoft/DNS-Challenge/tree/master/datasets
Challenge: https://www.microsoft.com/en-us/research/academic-program/deep-noise-suppression-challenge-icassp-2021/
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GitHub
GitHub - microsoft/DNS-Challenge: This repo contains the noscripts, models, and required files for the Deep Noise Suppression (DNS)…
This repo contains the noscripts, models, and required files for the Deep Noise Suppression (DNS) Challenge. - GitHub - microsoft/DNS-Challenge: This repo contains the noscripts, models, and required...
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📛Sharded: A New Technique To Double The Size Of PyTorch Models
Article: https://towardsdatascience.com/sharded-a-new-technique-to-double-the-size-of-pytorch-models-3af057466dba
Habr ru: https://habr.com/ru/company/skillfactory/blog/536394/
ZeRO: Memory Optimizations Paper: https://arxiv.org/abs/1910.02054
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Article: https://towardsdatascience.com/sharded-a-new-technique-to-double-the-size-of-pytorch-models-3af057466dba
Habr ru: https://habr.com/ru/company/skillfactory/blog/536394/
ZeRO: Memory Optimizations Paper: https://arxiv.org/abs/1910.02054
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🔝 Top 10 Computer Vision Papers 2020
https://www.kdnuggets.com/2021/01/top-10-computer-vision-papers-2020.html
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https://www.kdnuggets.com/2021/01/top-10-computer-vision-papers-2020.html
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Datasets
Datasets collected for network science, deep learning and general machine learning research.
Github: https://github.com/benedekrozemberczki/datasets
Paper: https://arxiv.org/abs/2101.03091v1
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Datasets collected for network science, deep learning and general machine learning research.
Github: https://github.com/benedekrozemberczki/datasets
Paper: https://arxiv.org/abs/2101.03091v1
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GitHub
GitHub - benedekrozemberczki/datasets: A repository of pretty cool datasets that I collected for network science and machine learning…
A repository of pretty cool datasets that I collected for network science and machine learning research. - benedekrozemberczki/datasets
FaceX-Zoo: A PyTorch Toolbox for Face Recognition
Github: https://github.com/JDAI-CV/faceX-Zoo
Paper: https://arxiv.org/abs/2101.04407v2
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Github: https://github.com/JDAI-CV/faceX-Zoo
Paper: https://arxiv.org/abs/2101.04407v2
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🪐 A Bayesian neural network predicts the dissolution of compact planetary systems
Post/code: https://astroautomata.com/paper/bnn-instability-model/
API: https://github.com/dtamayo/spock
Paper: https://arxiv.org/abs/2101.04117
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Post/code: https://astroautomata.com/paper/bnn-instability-model/
API: https://github.com/dtamayo/spock
Paper: https://arxiv.org/abs/2101.04117
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🔥 Fast convolutional neural networks on FPGAs with hls4ml
Github: https://github.com/fastmachinelearning/hls4ml
Paper: https://arxiv.org/abs/2101.05108v1
Documentation: https://fastmachinelearning.org/hls4ml/
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Github: https://github.com/fastmachinelearning/hls4ml
Paper: https://arxiv.org/abs/2101.05108v1
Documentation: https://fastmachinelearning.org/hls4ml/
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🦾 Robustness Gym is a Python evaluation toolkit for natural language processing.
Github: https://github.com/robustness-gym/robustness-gym
Paper: https://arxiv.org/abs/2101.04840v1
Project: https://robustnessgym.com/
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Github: https://github.com/robustness-gym/robustness-gym
Paper: https://arxiv.org/abs/2101.04840v1
Project: https://robustnessgym.com/
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Extreme Gradient Boosting (XGBoost) with R and Python
https://datascience-enthusiast.com/R/ML_python_R_part2.html
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https://datascience-enthusiast.com/R/ML_python_R_part2.html
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Pixellib is a library for performing segmentation of objects in images and videos.
Github: https://github.com/ayoolaolafenwa/PixelLib
Paper: https://vixra.org/abs/2101.0122
Documentation: https://pixellib.readthedocs.io/en/latest/
Video: https://www.youtube.com/watch?v=hxczTe9U8jY&feature=emb_logo&ab_channel=AyoolaOlafenwa
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Github: https://github.com/ayoolaolafenwa/PixelLib
Paper: https://vixra.org/abs/2101.0122
Documentation: https://pixellib.readthedocs.io/en/latest/
Video: https://www.youtube.com/watch?v=hxczTe9U8jY&feature=emb_logo&ab_channel=AyoolaOlafenwa
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🌳 Neural-Backed Decision Trees
Demo: https://research.alvinwan.com/neural-backed-decision-trees/
Github: https://github.com/alvinwan/neural-backed-decision-trees
Paper: https://arxiv.org/abs/2004.00221
Code: https://colab.research.google.com/github/alvinwan/neural-backed-decision-trees/blob/master/examples/load_pretrained_nbdts.ipynb
Dataset: https://pytorch.org/docs/stable/torchvision/datasets.html
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Demo: https://research.alvinwan.com/neural-backed-decision-trees/
Github: https://github.com/alvinwan/neural-backed-decision-trees
Paper: https://arxiv.org/abs/2004.00221
Code: https://colab.research.google.com/github/alvinwan/neural-backed-decision-trees/blob/master/examples/load_pretrained_nbdts.ipynb
Dataset: https://pytorch.org/docs/stable/torchvision/datasets.html
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🐍 Machine Learning From Scratch In Python - Full Course With 12 Algorithms
Video: https://www.youtube.com/watch?v=rLOyrWV8gmA&ab_channel=PythonEngineer
Code: https://github.com/python-engineer/MLfromscratch/tree/master/mlfromscratch
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Video: https://www.youtube.com/watch?v=rLOyrWV8gmA&ab_channel=PythonEngineer
Code: https://github.com/python-engineer/MLfromscratch/tree/master/mlfromscratch
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🧍 TIN: Transferable Interactiveness Network
Github: https://github.com/DirtyHarryLYL/Transferable-Interactiveness-Network
HOI-Learning-List: https://github.com/DirtyHarryLYL/HOI-Learning-List
Paper: https://arxiv.org/abs/2101.10292v1
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Github: https://github.com/DirtyHarryLYL/Transferable-Interactiveness-Network
HOI-Learning-List: https://github.com/DirtyHarryLYL/HOI-Learning-List
Paper: https://arxiv.org/abs/2101.10292v1
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Bottleneck Transformer - Pytorch
Github: https://github.com/lucidrains/bottleneck-transformer-pytorch
Bottleneck Transformers : https://github.com/leaderj1001/BottleneckTransformers
Paper: https://arxiv.org/abs/2101.11605v1
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Github: https://github.com/lucidrains/bottleneck-transformer-pytorch
Bottleneck Transformers : https://github.com/leaderj1001/BottleneckTransformers
Paper: https://arxiv.org/abs/2101.11605v1
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💻 Learning to Reason Over Tables from Less Data
Google research: https://ai.googleblog.com/2021/01/learning-to-reason-over-tables-from.html
Code: https://github.com/google-research/tapas
Colab: https://colab.research.google.com/github/google-research/tapas/blob/master/notebooks/tabfact_predictions.ipynb
Dataset: https://www.microsoft.com/en-us/download/details.aspx?id=54253
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Google research: https://ai.googleblog.com/2021/01/learning-to-reason-over-tables-from.html
Code: https://github.com/google-research/tapas
Colab: https://colab.research.google.com/github/google-research/tapas/blob/master/notebooks/tabfact_predictions.ipynb
Dataset: https://www.microsoft.com/en-us/download/details.aspx?id=54253
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