DD-Net

🖥 Github: https://github.com/fandulu/DD-Net

📕 Paper: https://arxiv.org/pdf/1907.09658.pdf

🔥 Datasets: https://paperswithcode.com/dataset/gtea

https://t.iss.one/DataScienceT

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✅ Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model

🖥 Github: https://github.com/sudo-ai-3d/zero123plus

📕 Paper: https://arxiv.org/abs/2310.15110v1

⭐️ Demo: https://huggingface.co/spaces/sudo-ai/zero123plus-demo-space

🚀Dataset: https://paperswithcode.com/dataset/shapenet

https://t.iss.one/DataScienceT

This channels is for Programmers, Coders, Software Engineers.

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1- Data Science
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3- Data Visualization
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SplitGNN

🖥 Github: https://github.com/blackboxo/SplitGNN

📕 Paper: https://dl.acm.org/doi/pdf/10.1145/3583780.3615067

🔥 Datasets: https://paperswithcode.com/dataset/fdcompcn

https://t.iss.one/DataScienceT

SALMONN: Speech Audio Language Music Open Neural Network

🖥 Github: https://github.com/bytedance/salmonn

📕 Paper: https://arxiv.org/pdf/2310.13289v1.pdf

🔥 Datasets: https://paperswithcode.com/dataset/librispeech

https://t.iss.one/DataScienceT

[NeurIPS 2023] Global Structure-Aware Diffusion Process for Low-Light Image Enhancement

🖥 Github: https://github.com/jinnh/GSAD

📕 Paper: https://arxiv.org/pdf/2310.17577.pdf

🔥 Datasets: https://paperswithcode.com/dataset/lol

CS25: Transformers United V3

New lectures on the course on Transformers from Stanford! Stanford CS 25 " Transformers United " featured celebrity guests such as Andriy Karpaty, Noam Brown, Lukas Beyer and Geoff Hinton himself!

A new report has been released on the creation and recipes for creating universal AI agents in open worlds:

🟢 MineDojo : an open framework and multimodal database for training Minecraft agents.

🟢 Voyager : agent for lifelong learning in Minecraft based on LLM.

🟢 Eureka: GPT-4 develops reward functions to teach a robot hand to turn a knob.

🟢 VIMA : one of the earliest multimodal LLMs.

🟢A look into the future: promising areas of research.

☑️ Slides : https://drive.google.com/file/d/1lWIhijUaTZkkWOC_YwZHMoI0h7EAWVPL/view

📑 Lectures : https://web.stanford.edu/class/cs25

👌 https://t.iss.one/CodeProgrammer

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☑ PERF: Panoramic Neural Radiance Field from a Single Panorama

🖥 Github: https://github.com/perf-project/PeRF

⚡️Project: https://perf-project.github.io/

📕 Paper: https://arxiv.org/abs/2310.16831v1

⏩ Dataset: https://paperswithcode.com/dataset/replica

https://t.iss.one/DataScienceT

Human-Guided Complexity-Controlled Abstractions

🖥 Github: https://github.com/mycal-tucker/human-guided-abstractions

📕 Paper: https://arxiv.org/pdf/2310.17550v1.pdf

🔥 Datasets: https://paperswithcode.com/dataset/fashion-mnist

https://t.iss.one/DataScienceT

DialogLLMScenic

🖥 Github: https://github.com/avmb/dialogllmscenic

📕 Paper: https://arxiv.org/pdf/2310.17372v1.pdf

🔥 Datasets: https://paperswithcode.com/dataset/carla

⭐ Tasks: https://paperswithcode.com/task/self-driving-cars

https://t.iss.one/DataScienceT

⚡️ LLMRec: Large Language Models with Graph Augmentation for Recommendation

🖥 Github: https://github.com/hkuds/llmrec

📕 Paper: https://arxiv.org/abs/2311.00423v1

⏩ Project: https://llmrec.github.io/

🌐 Dataset: https://llmrec.github.io/#

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🖥 TORCH UNCERTAINTY

Comprehensive PyTorch Library for deep learning uncertainty quantification techniques.

pip install torch-uncertainty

🖥 Github: https://github.com/ensta-u2is/torch-uncertainty

📕 Paper: https://arxiv.org/abs/2311.01434v1

⏩ Project: https://llmrec.github.io/

👣 Api: https://torch-uncertainty.github.io/api.html

🌐 Dataset: https://paperswithcode.com/dataset/cifar-10

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PETA: Evaluating the Impact of Protein Transfer Learning with Sub-word Tokenization on Downstream Applications

🖥 Github: https://github.com/ginnm/proteinpretraining

📕 Paper: https://arxiv.org/pdf/2310.17415v1.pdf

🔥 Datasets: https://paperswithcode.com/dataset/peta-protein

⭐ Tasks: https://paperswithcode.com/task/language-modelling

https://t.iss.one/DataScienceT

🎧 Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer model

Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer model.

🖥 Github: https://github.com/amaai-lab/video2music

📕 Paper: https://arxiv.org/abs/2311.00968v1

⏩ Demo: https://llmrec.github.io/

🌐 Dataset: https://zenodo.org/records/10057093

https://t.iss.one/DataScienceT