AdaVAE: Exploring Adaptive GPT-2s in Variational Auto-Encoders for Language Modeling
First VAE framework empowered with adaptive GPT-2s (AdaVAE).
Github: https://github.com/ImKeTT/adavae
Paper: https://arxiv.org/abs/2205.05862v1
Task: https://paperswithcode.com/task/representation-learning
First VAE framework empowered with adaptive GPT-2s (AdaVAE).
Github: https://github.com/ImKeTT/adavae
Paper: https://arxiv.org/abs/2205.05862v1
Task: https://paperswithcode.com/task/representation-learning
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Efficient and performance-portable vector software
CPUs provide SIMD/vector instructions that apply the same operation to multiple data items. This can reduce energy usage e.g. fivefold because fewer instructions are executed. We also often see 5-10x speedups.
Code: https://github.com/google/highway
Paper: https://arxiv.org/abs/2205.05982v1
Testing: https://github.com/google/highway/blob/master/g3doc/release_testing_process.md
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CPUs provide SIMD/vector instructions that apply the same operation to multiple data items. This can reduce energy usage e.g. fivefold because fewer instructions are executed. We also often see 5-10x speedups.
Code: https://github.com/google/highway
Paper: https://arxiv.org/abs/2205.05982v1
Testing: https://github.com/google/highway/blob/master/g3doc/release_testing_process.md
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[RK-Net]Joint Representation Learning and Keypoint Detection for Cross-view Geo-localization
Github: https://github.com/AggMan96/RK-Net
Paper: https://zhunzhong.site/paper/RK_Net.pdf
Dataset: https://paperswithcode.com/dataset/university-1652
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Github: https://github.com/AggMan96/RK-Net
Paper: https://zhunzhong.site/paper/RK_Net.pdf
Dataset: https://paperswithcode.com/dataset/university-1652
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Group R-CNN for Point-based Weakly Semi-supervised Object Detection
Instance-aware representation learning which consists of instance-aware feature enhancement and instance-aware parameter generation to overcome this issue.
Code: https://github.com/jshilong/grouprcnn
Installation: https://mmdetection.readthedocs.io/en/v2.18.1/get_started.html#installation
Paper: https://arxiv.org/abs/2205.05920v1
Task: https://paperswithcode.com/task/object-detection
Dataset: https://paperswithcode.com/dataset/coco
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Instance-aware representation learning which consists of instance-aware feature enhancement and instance-aware parameter generation to overcome this issue.
Code: https://github.com/jshilong/grouprcnn
Installation: https://mmdetection.readthedocs.io/en/v2.18.1/get_started.html#installation
Paper: https://arxiv.org/abs/2205.05920v1
Task: https://paperswithcode.com/task/object-detection
Dataset: https://paperswithcode.com/dataset/coco
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Towards Unified Keyframe Propagation Models
A two-stream approach, where high-frequency features interact locally and low-frequency features interact globally.
Github: https://github.com/runwayml/guided-inpainting
Paper: https://arxiv.org/abs/2205.09731v1
Dataset: https://paperswithcode.com/dataset/places
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A two-stream approach, where high-frequency features interact locally and low-frequency features interact globally.
Github: https://github.com/runwayml/guided-inpainting
Paper: https://arxiv.org/abs/2205.09731v1
Dataset: https://paperswithcode.com/dataset/places
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👀 Sockeye
Sockeye is an open-source sequence-to-sequence framework for Neural Machine Translation built on PyTorch.
Code: https://github.com/awslabs/sockeye
Tutorial: https://github.com/awslabs/sockeye/blob/main/docs/tutorials/wmt_large.md
Paper: https://arxiv.org/abs/2205.06618v1
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Sockeye is an open-source sequence-to-sequence framework for Neural Machine Translation built on PyTorch.
Code: https://github.com/awslabs/sockeye
Tutorial: https://github.com/awslabs/sockeye/blob/main/docs/tutorials/wmt_large.md
Paper: https://arxiv.org/abs/2205.06618v1
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🖇 A graph-transformer for whole slide image classification
Graph-Transformer (GT) that fuses a graph-based representation of an WSI and a vision transformer for processing pathology images.
Github: https://github.com/vkola-lab/tmi2022
Paper: https://arxiv.org/abs/2205.09671v1
Dataset: https://paperswithcode.com/dataset/imagenet
Graph-Transformer (GT) that fuses a graph-based representation of an WSI and a vision transformer for processing pathology images.
Github: https://github.com/vkola-lab/tmi2022
Paper: https://arxiv.org/abs/2205.09671v1
Dataset: https://paperswithcode.com/dataset/imagenet
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☑️ TorchSSL
A Pytorch-based toolbox for semi-supervised learning.
Code: https://github.com/torchssl/torchssl
Paper: https://arxiv.org/abs/2205.07246v1
Logs and weights: https://onedrive.live.com/?authkey=%21AJ%2DwKMa%2DENcbk1s&id=AF426F3217F6565A%213488&cid=AF426F3217F6565A
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A Pytorch-based toolbox for semi-supervised learning.
Code: https://github.com/torchssl/torchssl
Paper: https://arxiv.org/abs/2205.07246v1
Logs and weights: https://onedrive.live.com/?authkey=%21AJ%2DwKMa%2DENcbk1s&id=AF426F3217F6565A%213488&cid=AF426F3217F6565A
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RankGen - Improving Text Generation with Large Ranking Models
RankGen is a 1.2 billion encoder model which maps prefixes and generations from any language model (in continutation to the prefix) to a shared vector space.
Github: https://github.com/martiansideofthemoon/rankgen
Paper: https://arxiv.org/abs/2205.09726
Dataset: https://paperswithcode.com/dataset/imagenet
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RankGen is a 1.2 billion encoder model which maps prefixes and generations from any language model (in continutation to the prefix) to a shared vector space.
Github: https://github.com/martiansideofthemoon/rankgen
Paper: https://arxiv.org/abs/2205.09726
Dataset: https://paperswithcode.com/dataset/imagenet
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🧍♂ AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars
Github: https://github.com/hongfz16/avatarclip
Colab demo: https://colab.research.google.com/drive/1dfaecX7xF3nP6fyXc8XBljV5QY1lc1TR?usp=sharing
Paper: https://arxiv.org/abs/2205.08535v1
Dataset: https://paperswithcode.com/dataset/amass
Instructions: https://github.com/hongfz16/AvatarCLIP/blob/main/Avatar2FBX/README.md
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Github: https://github.com/hongfz16/avatarclip
Colab demo: https://colab.research.google.com/drive/1dfaecX7xF3nP6fyXc8XBljV5QY1lc1TR?usp=sharing
Paper: https://arxiv.org/abs/2205.08535v1
Dataset: https://paperswithcode.com/dataset/amass
Instructions: https://github.com/hongfz16/AvatarCLIP/blob/main/Avatar2FBX/README.md
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☠️ PYSKL: Towards Good Practices for Skeleton Action Recognition
Skeleton-based action recognition
Github: https://github.com/kennymckormick/pyskl
Paper: https://arxiv.org/abs/2205.09443v1
Dataset: https://paperswithcode.com/dataset/finegym
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Skeleton-based action recognition
Github: https://github.com/kennymckormick/pyskl
Paper: https://arxiv.org/abs/2205.09443v1
Dataset: https://paperswithcode.com/dataset/finegym
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The Complete Collection of Data Science Books – Part 1
https://www.kdnuggets.com/2022/05/complete-collection-data-science-books-part-1.html
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https://www.kdnuggets.com/2022/05/complete-collection-data-science-books-part-1.html
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📝 Automated Crossword Solving
Pretrained models, precomputed FAISS embeddings, and a crossword clue-answer dataset.
Github: https://github.com/albertkx/berkeley-crossword-solver
Paper: https://arxiv.org/abs/2205.09665v1
Dataset: https://www.xwordinfo.com/JSON/
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Pretrained models, precomputed FAISS embeddings, and a crossword clue-answer dataset.
Github: https://github.com/albertkx/berkeley-crossword-solver
Paper: https://arxiv.org/abs/2205.09665v1
Dataset: https://www.xwordinfo.com/JSON/
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🦄 Imagen unprecedented photorealism × deep level of language understanding From Google
Home: https://gweb-research-imagen.appspot.com/
Paper: https://gweb-research-imagen.appspot.com/paper.pdf
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Home: https://gweb-research-imagen.appspot.com/
Paper: https://gweb-research-imagen.appspot.com/paper.pdf
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⚙️ Time-series Transformer Generative Adversarial Networks
Github: https://github.com/jsyoon0823/TimeGAN
Paper: https://arxiv.org/abs/2205.11164v1
Stock data: https://finance.yahoo.com/quote/GOOG/history
Energy data: http://archive.ics.uci.edu/ml/datasets/Appliances+energy+prediction
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Github: https://github.com/jsyoon0823/TimeGAN
Paper: https://arxiv.org/abs/2205.11164v1
Stock data: https://finance.yahoo.com/quote/GOOG/history
Energy data: http://archive.ics.uci.edu/ml/datasets/Appliances+energy+prediction
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💻 BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework
Github: https://github.com/adlab-autodrive/bevfusion
Paper: https://arxiv.org/abs/2205.13790v1
Dataset: https://paperswithcode.com/dataset/kitti
Github: https://github.com/adlab-autodrive/bevfusion
Paper: https://arxiv.org/abs/2205.13790v1
Dataset: https://paperswithcode.com/dataset/kitti
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📍 Perturbation Augmentation for Fairer NLP
Responsible NLP projects from Meta AI.
Github: https://github.com/facebookresearch/responsiblenlp
Paper: https://arxiv.org/abs/2205.12586v1
Dataset: https://paperswithcode.com/dataset/glue
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Responsible NLP projects from Meta AI.
Github: https://github.com/facebookresearch/responsiblenlp
Paper: https://arxiv.org/abs/2205.12586v1
Dataset: https://paperswithcode.com/dataset/glue
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🟢 Green Hierarchical Vision Transformer for Masked Image Modeling
Github: https://github.com/layneh/greenmim
Paper: https://arxiv.org/abs/2205.13515v1
Dataset: https://paperswithcode.com/dataset/coco
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Github: https://github.com/layneh/greenmim
Paper: https://arxiv.org/abs/2205.13515v1
Dataset: https://paperswithcode.com/dataset/coco
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🔻 AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition
Github: https://github.com/ShoufaChen/AdaptFormer
Paper: https://arxiv.org/abs/2205.13535v1
Dataset: https://paperswithcode.com/dataset/something-something-v2
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Github: https://github.com/ShoufaChen/AdaptFormer
Paper: https://arxiv.org/abs/2205.13535v1
Dataset: https://paperswithcode.com/dataset/something-something-v2
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