🔥 Astrologers have announced a week of video generation models!
Following the hype around the Kling, Luma and Runway models, a new open source version of Open-Sora has been released.
Open-Sora 1.2 from Hpcoretech has been published on huggingface.
Basic moments:
The new 1.1B model is trained on 20M videos and generates videos up to 14 seconds long at 720p resolution.
▪Diffusion Model: https://huggingface.co/hpcai-tech/OpenSora-STDiT-v3
▪VAE model: https://huggingface.co/hpcai-tech/OpenSora-VAE-v1.2
▪Technical report: https://github.com/hpcaitech/Open-Sora/blob/main/docs/report_03.md
▪Demo: https://huggingface.co/spaces/hpcai-tech/open-sora
@Machine_learn
Following the hype around the Kling, Luma and Runway models, a new open source version of Open-Sora has been released.
Open-Sora 1.2 from Hpcoretech has been published on huggingface.
Basic moments:
The new 1.1B model is trained on 20M videos and generates videos up to 14 seconds long at 720p resolution.
▪Diffusion Model: https://huggingface.co/hpcai-tech/OpenSora-STDiT-v3
▪VAE model: https://huggingface.co/hpcai-tech/OpenSora-VAE-v1.2
▪Technical report: https://github.com/hpcaitech/Open-Sora/blob/main/docs/report_03.md
▪Demo: https://huggingface.co/spaces/hpcai-tech/open-sora
@Machine_learn
MajorTom-Core-S1RTC is a new satellite image standard and dataset that contains 1,469,955 images.
16 TB of radiometrically calibrated images.
▪ HF: https://huggingface.co/Major-TOM
▪ Github: https://github.com/ESA-PhiLab/Major-TOM/
▪ Colab: https://colab.research.google.com/github/ESA-PhiLab/Major-TOM/blob/main/03-Filtering-in-Colab.ipynb
▪ Paper: https://www.arxiv.org/abs/2402.12095
▪ MajorTOM-Core-Viewer: https://huggingface.co/spaces/Major-TOM/MajorTOM-Core-Viewer
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TSI-Bench: Benchmarking Time Series Imputation
🖥 Github: https://github.com/WenjieDu/Awesome_Imputation
📕 Paper: https://arxiv.org/pdf/2406.12747v1.pdf
🔥Dataset: https://github.com/WenjieDu/TSDB
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🔥Dataset: https://github.com/WenjieDu/TSDB
@Machine_learn
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با عرض سلام پك يادگيري ماشين و يادگيري عميق به همراه ٣٦ پروژه با داكيومنت فارسي رو براي دوستان تهيه كرديم از دوستان كسي خواست مي تونه به ايدي بنده پيام بده.
1-Deep Learning Basic
-01_Introduction
--01_How_TensorFlow_Works
--02_Creating_and_Using_Tensors
--03_Implementing_Activation_Functions
-02_TensorFlow_Way
--01_Operations_as_a_Computational_Graph
--02_Implementing_Loss_Functions
--03_Implementing_Back_Propagation
--04_Working_with_Batch_and_Stochastic_Training
--05_Evaluating_Models
-03_Linear_Regression
--linear regression
--Logistic Regression
-04_Neural_Networks
--01_Introduction
--02_Single_Hidden_Layer_Network
--03_Using_Multiple_Layers
-05_Convolutional_Neural_Networks
--Convolution Neural Networks
--Convolutional Neural Networks Tensorflow
--TFRecord For Deep learning Models
-06_Recurrent_Neural_Networks
--Recurrent Neural Networks (RNN)
2-Classification apparel
-Classification apparel double capsule
-Classification apparel double cnn
3-ALZHEIMERS USING CNN(ResNet)
4-Fake News (Covid-19 dataset)
-Multi-channel
-3DCNN model
-Base line+ Char CNN
-Fake News Covid CapsuleNet
5-3DCNN Fake News
6-recommender systems
-GRU+LSTM MovieLens
7-Multi-Domain Sentiment Analysis
-Dranziera CapsuleNet
-Dranziera CNN Multi-channel
-Dranziera LSTM
8-Persian Multi-Domain SA
-Bi-GRU Capsule Net
-Multi-CNN
9-Recommendation system
-Factorization Recommender, Ranking Factorization Recommender, Item Similarity Recommender (turicreate)
-SVD, SVD++, NMF, Slope One, k-NN, Centered k-NN, k-NN Baseline, Co-Clustering(surprise)
10-NihX-Ray
-optimized CNN on FullDataset Nih-Xray
-MobileNet
-Transfer learning
-Capsule Network on FullDataset Nih-Xray
@Raminmousa
1-Deep Learning Basic
-01_Introduction
--01_How_TensorFlow_Works
--02_Creating_and_Using_Tensors
--03_Implementing_Activation_Functions
-02_TensorFlow_Way
--01_Operations_as_a_Computational_Graph
--02_Implementing_Loss_Functions
--03_Implementing_Back_Propagation
--04_Working_with_Batch_and_Stochastic_Training
--05_Evaluating_Models
-03_Linear_Regression
--linear regression
--Logistic Regression
-04_Neural_Networks
--01_Introduction
--02_Single_Hidden_Layer_Network
--03_Using_Multiple_Layers
-05_Convolutional_Neural_Networks
--Convolution Neural Networks
--Convolutional Neural Networks Tensorflow
--TFRecord For Deep learning Models
-06_Recurrent_Neural_Networks
--Recurrent Neural Networks (RNN)
2-Classification apparel
-Classification apparel double capsule
-Classification apparel double cnn
3-ALZHEIMERS USING CNN(ResNet)
4-Fake News (Covid-19 dataset)
-Multi-channel
-3DCNN model
-Base line+ Char CNN
-Fake News Covid CapsuleNet
5-3DCNN Fake News
6-recommender systems
-GRU+LSTM MovieLens
7-Multi-Domain Sentiment Analysis
-Dranziera CapsuleNet
-Dranziera CNN Multi-channel
-Dranziera LSTM
8-Persian Multi-Domain SA
-Bi-GRU Capsule Net
-Multi-CNN
9-Recommendation system
-Factorization Recommender, Ranking Factorization Recommender, Item Similarity Recommender (turicreate)
-SVD, SVD++, NMF, Slope One, k-NN, Centered k-NN, k-NN Baseline, Co-Clustering(surprise)
10-NihX-Ray
-optimized CNN on FullDataset Nih-Xray
-MobileNet
-Transfer learning
-Capsule Network on FullDataset Nih-Xray
@Raminmousa
Consistency Models Made Easy
🖥 Github: https://github.com/locuslab/ect
📕 Paper: https://arxiv.org/abs/2406.14548v1
🔥Dataset: https://paperswithcode.com/dataset/cifar-10
@Machine_learn
🔥Dataset: https://paperswithcode.com/dataset/cifar-10
@Machine_learn
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LangSuitE: Planning, Controlling and Interacting with Large Language Models in Embodied Text Environments
🖥 Github: https://github.com/bigai-nlco/langsuite
📕 Paper: https://arxiv.org/abs/2406.16294v1
🔥Dataset: https://paperswithcode.com/dataset/ai2-thor
@Machine_learn
🔥Dataset: https://paperswithcode.com/dataset/ai2-thor
@Machine_learn
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Point-SAM: Promptable 3D Segmentation Model for Point Clouds
🖥 Github: https://github.com/zyc00/point-sam
📕 Paper: https://arxiv.org/abs/2406.17741v1
🔥Dataset: https://paperswithcode.com/dataset/shapenet
@Machine_learn
🔥Dataset: https://paperswithcode.com/dataset/shapenet
@Machine_learn
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با عرض سلام پك يادگيري ماشين و يادگيري عميق به همراه ٣٦ پروژه با داكيومنت فارسي رو براي دوستان تهيه كرديم از دوستان كسي خواست مي تونه به ايدي بنده پيام بده.
1-Deep Learning Basic
-01_Introduction
--01_How_TensorFlow_Works
--02_Creating_and_Using_Tensors
--03_Implementing_Activation_Functions
-02_TensorFlow_Way
--01_Operations_as_a_Computational_Graph
--02_Implementing_Loss_Functions
--03_Implementing_Back_Propagation
--04_Working_with_Batch_and_Stochastic_Training
--05_Evaluating_Models
-03_Linear_Regression
--linear regression
--Logistic Regression
-04_Neural_Networks
--01_Introduction
--02_Single_Hidden_Layer_Network
--03_Using_Multiple_Layers
-05_Convolutional_Neural_Networks
--Convolution Neural Networks
--Convolutional Neural Networks Tensorflow
--TFRecord For Deep learning Models
-06_Recurrent_Neural_Networks
--Recurrent Neural Networks (RNN)
2-Classification apparel
-Classification apparel double capsule
-Classification apparel double cnn
3-ALZHEIMERS USING CNN(ResNet)
4-Fake News (Covid-19 dataset)
-Multi-channel
-3DCNN model
-Base line+ Char CNN
-Fake News Covid CapsuleNet
5-3DCNN Fake News
6-recommender systems
-GRU+LSTM MovieLens
7-Multi-Domain Sentiment Analysis
-Dranziera CapsuleNet
-Dranziera CNN Multi-channel
-Dranziera LSTM
8-Persian Multi-Domain SA
-Bi-GRU Capsule Net
-Multi-CNN
9-Recommendation system
-Factorization Recommender, Ranking Factorization Recommender, Item Similarity Recommender (turicreate)
-SVD, SVD++, NMF, Slope One, k-NN, Centered k-NN, k-NN Baseline, Co-Clustering(surprise)
10-NihX-Ray
-optimized CNN on FullDataset Nih-Xray
-MobileNet
-Transfer learning
-Capsule Network on FullDataset Nih-Xray
@Raminmousa
1-Deep Learning Basic
-01_Introduction
--01_How_TensorFlow_Works
--02_Creating_and_Using_Tensors
--03_Implementing_Activation_Functions
-02_TensorFlow_Way
--01_Operations_as_a_Computational_Graph
--02_Implementing_Loss_Functions
--03_Implementing_Back_Propagation
--04_Working_with_Batch_and_Stochastic_Training
--05_Evaluating_Models
-03_Linear_Regression
--linear regression
--Logistic Regression
-04_Neural_Networks
--01_Introduction
--02_Single_Hidden_Layer_Network
--03_Using_Multiple_Layers
-05_Convolutional_Neural_Networks
--Convolution Neural Networks
--Convolutional Neural Networks Tensorflow
--TFRecord For Deep learning Models
-06_Recurrent_Neural_Networks
--Recurrent Neural Networks (RNN)
2-Classification apparel
-Classification apparel double capsule
-Classification apparel double cnn
3-ALZHEIMERS USING CNN(ResNet)
4-Fake News (Covid-19 dataset)
-Multi-channel
-3DCNN model
-Base line+ Char CNN
-Fake News Covid CapsuleNet
5-3DCNN Fake News
6-recommender systems
-GRU+LSTM MovieLens
7-Multi-Domain Sentiment Analysis
-Dranziera CapsuleNet
-Dranziera CNN Multi-channel
-Dranziera LSTM
8-Persian Multi-Domain SA
-Bi-GRU Capsule Net
-Multi-CNN
9-Recommendation system
-Factorization Recommender, Ranking Factorization Recommender, Item Similarity Recommender (turicreate)
-SVD, SVD++, NMF, Slope One, k-NN, Centered k-NN, k-NN Baseline, Co-Clustering(surprise)
10-NihX-Ray
-optimized CNN on FullDataset Nih-Xray
-MobileNet
-Transfer learning
-Capsule Network on FullDataset Nih-Xray
@Raminmousa
🏥 MedMNIST-C: benchmark dataset based on the MedMNIST+ collection covering 12 2D datasets and 9 imaging modalities.
🖥 Github: https://github.com/francescodisalvo05/medmnistc-api
📕 Paper: https://arxiv.org/abs/2406.17536v2
🔥Dataset: https://paperswithcode.com/dataset/imagenet-c
@Machine_learn
pip install medmnistc
🔥Dataset: https://paperswithcode.com/dataset/imagenet-c
@Machine_learn
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🌟 SEE-2-SOUND - a method for generating complex spatial sound based on images and videos
— pip install see2sound
🖥 GitHub
🟡 Hugging Face
🟡 Arxiv
@Machine_learn
— pip install see2sound
🖥 GitHub
🟡 Hugging Face
🟡 Arxiv
@Machine_learn
Seq2Seq: Sequence-to-Sequence Generator
🖥 Github: https://github.com/fiy2w/mri_seq2seq
📕 Paper: https://arxiv.org/abs/2407.02911v1
🔥Dataset: https://paperswithcode.com/task/contrastive-learning
@Machine_learn
🖥 Github: https://github.com/fiy2w/mri_seq2seq
📕 Paper: https://arxiv.org/abs/2407.02911v1
🔥Dataset: https://paperswithcode.com/task/contrastive-learning
@Machine_learn
سلام دوستانی که مقاله دارن می تونن به این ژورنال بفرستن و من و به عنوان داور معرفی کنن
@Machine_learn
@Machine_learn
Minutes to Seconds: Speeded-up DDPM-based Image Inpainting with Coarse-to-Fine Sampling
🖥 Github: https://github.com/linghuyuhangyuan/m2s
📕 Paper: https://arxiv.org/abs/2407.05875v1
🔥Dataset: https://paperswithcode.com/task/denoising
@Machine_learn
🔥Dataset: https://paperswithcode.com/task/denoising
@Machine_learn
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👁🗨 LongVA: Long Context Transfer from Language to Vision
▪Github: https://github.com/EvolvingLMMs-Lab/LongVA
▪Paper: https://arxiv.org/abs/2406.16852
▪Project: https://lmms-lab.github.io/posts/longva/
▪Demo: https://longva-demo.lmms-lab.com/
@Machine_learn
▪Github: https://github.com/EvolvingLMMs-Lab/LongVA
▪Paper: https://arxiv.org/abs/2406.16852
▪Project: https://lmms-lab.github.io/posts/longva/
▪Demo: https://longva-demo.lmms-lab.com/
@Machine_learn
Unified Embedding Alignment for Open-Vocabulary Video Instance Segmentation (ECCV 2024)
🖥 Github: https://github.com/fanghaook/ovformer
📕 Paper: https://arxiv.org/abs/2407.07427v1
@Machine_learn
@Machine_learn
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Multimodal contrastive learning for spatial gene expression prediction using histology images
🖥 Github: https://github.com/modelscope/data-juicer
📕 Paper: https://arxiv.org/abs/2407.08583v1
🚀 Dataset: https://paperswithcode.com/dataset/coco
@Machine_learn
🚀 Dataset: https://paperswithcode.com/dataset/coco
@Machine_learn
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