PG-RCNN: Semantic Surface Point Generation for 3D Object Detection (ICCV 2023)
🖥 Github: https://github.com/quotation2520/pg-rcnn
📕 Paper: https://arxiv.org/pdf/2307.12637v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/kitti
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/quotation2520/pg-rcnn
📕 Paper: https://arxiv.org/pdf/2307.12637v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/kitti
https://t.iss.one/DataScienceT
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🦩 OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models
An open-source framework for training large multimodal models.
🖥 Github: https://github.com/mlfoundations/open_flamingo
📕 Paper: https://arxiv.org/abs/2308.01390
⭐️ Demo: https://huggingface.co/spaces/openflamingo/OpenFlamingo
☑️ Dataset: https://paperswithcode.com/dataset/flickr30k
https://t.iss.one/DataScienceT
An open-source framework for training large multimodal models.
pip install open-flamingo🖥 Github: https://github.com/mlfoundations/open_flamingo
📕 Paper: https://arxiv.org/abs/2308.01390
⭐️ Demo: https://huggingface.co/spaces/openflamingo/OpenFlamingo
☑️ Dataset: https://paperswithcode.com/dataset/flickr30k
https://t.iss.one/DataScienceT
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✅ LISA: Reasoning Segmentation via Large Language Model
New segmentation task -- reasoning segmentation. The task is designed to output a segmentation mask given a complex and implicit query text.
🖥 Github: https://github.com/dvlab-research/lisa
📕 Paper: https://arxiv.org/abs/2308.00692v2
☑️ Dataset: https://github.com/dvlab-research/lisa#dataset
https://t.iss.one/DataScienceT
New segmentation task -- reasoning segmentation. The task is designed to output a segmentation mask given a complex and implicit query text.
🖥 Github: https://github.com/dvlab-research/lisa
📕 Paper: https://arxiv.org/abs/2308.00692v2
☑️ Dataset: https://github.com/dvlab-research/lisa#dataset
https://t.iss.one/DataScienceT
👍7
Forwarded from Data Science Books
Machine Learning with Python Cookbook (2023)
This book is available now only in paid channel
Cost of Paid channel is 5$ for one time and forever
Channel link: https://t.iss.one/+LnCmAFJO3tNmYjUy
Paid channel contain important book and udemy and other courses as zip files
Welcome all
Contact @Hussein_sheikho
This book is available now only in paid channel
Cost of Paid channel is 5$ for one time and forever
Channel link: https://t.iss.one/+LnCmAFJO3tNmYjUy
Paid channel contain important book and udemy and other courses as zip files
Welcome all
Contact @Hussein_sheikho
👍6👎2❤1
Rule By Example: Harnessing Logical Rules for Explainable Hate Speech Detection
🖥 Github: https://github.com/chrisisking/rule-by-example
📕 Paper: https://arxiv.org/pdf/2307.12935v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/hatexplain
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/chrisisking/rule-by-example
📕 Paper: https://arxiv.org/pdf/2307.12935v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/hatexplain
https://t.iss.one/DataScienceT
👍6❤1
🌉Enhancing Visibility in Nighttime Haze Images Using Guided APSF and Gradient Adaptive Convolution
Experiments demonstrate that our method achieves a PSNR of 30.72dB, outperforming state-of-the-art methods by 14
on GTA5 nighttime haze dataset.
🖥 Github: https://github.com/jinyeying/nighttime_dehaze/tree/main
📕 Paper: https://arxiv.org/abs/2308.01738v1
☑️ Dataset: https://www.dropbox.com/sh/7qzmb3y9akejape/AABYf2ZAqn_5vmPsOPg7KqoMa?dl=0
https://t.iss.one/DataScienceT
Experiments demonstrate that our method achieves a PSNR of 30.72dB, outperforming state-of-the-art methods by 14
on GTA5 nighttime haze dataset.
🖥 Github: https://github.com/jinyeying/nighttime_dehaze/tree/main
📕 Paper: https://arxiv.org/abs/2308.01738v1
☑️ Dataset: https://www.dropbox.com/sh/7qzmb3y9akejape/AABYf2ZAqn_5vmPsOPg7KqoMa?dl=0
https://t.iss.one/DataScienceT
Learning Dynamic Query Combinations for Transformer-based Object Detection and Segmentation
🖥 Github: https://github.com/bytedance/dq-det
📕 Paper: https://arxiv.org/pdf/2307.12239v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/cityscapes
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/bytedance/dq-det
📕 Paper: https://arxiv.org/pdf/2307.12239v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/cityscapes
https://t.iss.one/DataScienceT
👍1
👁🗨 PyTorch Toolbox for Image Quality Assessment
An IQA toolbox with pure python and pytorch.
🖥 Github: https://github.com/chaofengc/iqa-pytorch
📕 Paper: https://arxiv.org/abs/2308.03060v1
🖥 Colab: https://colab.research.google.com/drive/14J3KoyrjJ6R531DsdOy5Bza5xfeMODi6?usp=sharing
☑️ Dataset: https://paperswithcode.com/dataset/koniq-10k
https://t.iss.one/DataScienceT
An IQA toolbox with pure python and pytorch.
🖥 Github: https://github.com/chaofengc/iqa-pytorch
📕 Paper: https://arxiv.org/abs/2308.03060v1
🖥 Colab: https://colab.research.google.com/drive/14J3KoyrjJ6R531DsdOy5Bza5xfeMODi6?usp=sharing
☑️ Dataset: https://paperswithcode.com/dataset/koniq-10k
https://t.iss.one/DataScienceT
❤5👍2
🚀 AgentBench: Evaluating LLMs as Agents.
AgentBench, a multi-dimensional evolving benchmark that currently consists of 8 distinct environments to assess LLM-as-Agent's reasoning and decision-making abilities in a multi-turn open-ended generation setting.
🖥 Github: https://github.com/thudm/agentbench
📕 Paper: https://arxiv.org/abs/2308.03688v1
☑️ Dataset: https://paperswithcode.com/dataset/alfworld
https://t.iss.one/DataScienceT
AgentBench, a multi-dimensional evolving benchmark that currently consists of 8 distinct environments to assess LLM-as-Agent's reasoning and decision-making abilities in a multi-turn open-ended generation setting.
🖥 Github: https://github.com/thudm/agentbench
📕 Paper: https://arxiv.org/abs/2308.03688v1
☑️ Dataset: https://paperswithcode.com/dataset/alfworld
https://t.iss.one/DataScienceT
👍3❤1
🪄Optimizing a Text-To-Speech model using 🤗 Transformers
🤗 Post: https://huggingface.co/blog/optimizing-bark
🖥 Colab: https://colab.research.google.com/github/ylacombe/notebooks/blob/main/Benchmark_Bark_HuggingFace.ipynb
⭐️ Bark: https://huggingface.co/docs/transformers/main/en/model_doc/bark#overview
https://t.iss.one/DataScienceT
🤗 Post: https://huggingface.co/blog/optimizing-bark
🖥 Colab: https://colab.research.google.com/github/ylacombe/notebooks/blob/main/Benchmark_Bark_HuggingFace.ipynb
⭐️ Bark: https://huggingface.co/docs/transformers/main/en/model_doc/bark#overview
https://t.iss.one/DataScienceT
❤🔥2👍1
EchoGLAD: Hierarchical Graph Neural Networks for Left Ventricle Landmark Detection on Echocardiograms
🖥 Github: https://github.com/DSL-Lab/echoglad
📕 Paper: https://arxiv.org/pdf/2307.12229v1.pdf
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/DSL-Lab/echoglad
📕 Paper: https://arxiv.org/pdf/2307.12229v1.pdf
https://t.iss.one/DataScienceT
FATRER
🖥 Github: https://github.com/ludybupt/FATRER
📕 Paper: https://arxiv.org/pdf/2307.12221v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/iemocap
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/ludybupt/FATRER
📕 Paper: https://arxiv.org/pdf/2307.12221v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/iemocap
https://t.iss.one/DataScienceT
👍3
Revisiting the Minimalist Approach to Offline Reinforcement Learning
🖥 Github: https://github.com/tinkoff-ai/rebrac
📕 Paper: https://arxiv.org/pdf/2305.09836v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/d4rl
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/tinkoff-ai/rebrac
📕 Paper: https://arxiv.org/pdf/2305.09836v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/d4rl
https://t.iss.one/DataScienceT
👍3❤1
🔥Platypus: Quick, Cheap, and Powerful Refinement of LLMs
Family of fine-tuned and merged LLMs that achieves the strongest performance and currently stands at first place in HuggingFace's
git clone https://github.com/lm-sys/FastChat.git
cd FastChat
🖥 Github: https://github.com/arielnlee/Platypus
💻 Project: https://platypus-llm.github.io/
📕 Paper: https://arxiv.org/abs/2308.07317v1
⭐️ Dataset: https://huggingface.co/datasets/garage-bAInd/Open-Platypus
https://t.iss.one/DataScienceT
Family of fine-tuned and merged LLMs that achieves the strongest performance and currently stands at first place in HuggingFace's
git clone https://github.com/lm-sys/FastChat.git
cd FastChat
🖥 Github: https://github.com/arielnlee/Platypus
💻 Project: https://platypus-llm.github.io/
📕 Paper: https://arxiv.org/abs/2308.07317v1
⭐️ Dataset: https://huggingface.co/datasets/garage-bAInd/Open-Platypus
https://t.iss.one/DataScienceT
👍3
Forwarded from Data Science Machine Learning Data Analysis
Encyclopedia of Data Science and Machine Learning (2023)
This book was released two days ago and this book is more than 3400 pages.
With this book, you can become a first-class professional data scientist
The price of the book is $3,400
To get a discount of up to 95%, contact me immediately
Contact @hussein_sheikho
This book was released two days ago and this book is more than 3400 pages.
With this book, you can become a first-class professional data scientist
The price of the book is $3,400
To get a discount of up to 95%, contact me immediately
Contact @hussein_sheikho
👍8👎4🏆1
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✍ EasyEdit: An Easy-to-use Knowledge Editing Framework for Large Language Models
EasyEdit, demonstrating that knowledge editing surpasses traditional fine-tuning in terms of reliability and generalization.
🖥 Github: https://github.com/zjunlp/easyedit
📕 Paper: https://arxiv.org/abs/2308.07269v1
⭐️ Demo: https://knowlm.zjukg.cn/demo_edit
🎓Online Tutorial: https://colab.research.google.com/drive/1zcj8YgeqttwkpfoHXz9O9_rWxFFufXSO?usp=sharing
☑️ Docs: https://zjunlp.gitbook.io/easyedit
🤓 Dataset: https://drive.google.com/file/d/1IVcf5ikpfKuuuYeedUGomH01i1zaWuI6/view?usp=sharing
https://t.iss.one/DataScienceT
EasyEdit, demonstrating that knowledge editing surpasses traditional fine-tuning in terms of reliability and generalization.
🖥 Github: https://github.com/zjunlp/easyedit
📕 Paper: https://arxiv.org/abs/2308.07269v1
⭐️ Demo: https://knowlm.zjukg.cn/demo_edit
🎓Online Tutorial: https://colab.research.google.com/drive/1zcj8YgeqttwkpfoHXz9O9_rWxFFufXSO?usp=sharing
☑️ Docs: https://zjunlp.gitbook.io/easyedit
🤓 Dataset: https://drive.google.com/file/d/1IVcf5ikpfKuuuYeedUGomH01i1zaWuI6/view?usp=sharing
https://t.iss.one/DataScienceT
👍4❤1