Video Mamba Suite: State Space Model as a Versatile Alternative for Video Understanding
🖥 Github: https://github.com/opengvlab/video-mamba-suite
📕 Paper: https://arxiv.org/abs/2403.09626v1
🔥Dataset: https://paperswithcode.com/dataset/egoschema
@Machine_learn
🖥 Github: https://github.com/opengvlab/video-mamba-suite
📕 Paper: https://arxiv.org/abs/2403.09626v1
🔥Dataset: https://paperswithcode.com/dataset/egoschema
@Machine_learn
👍1
با عرض سلام نياز به نفر دوم اين مقاله داريم.
ابتدا اركايو مقاله تا دو هفته ديگه فرستاده ميشه سپس براي Knowledge-based Systems فرستاده ميشه. كسايي كه نياز دارن به بنده مراجعه كنن
@Raminmousa
ابتدا اركايو مقاله تا دو هفته ديگه فرستاده ميشه سپس براي Knowledge-based Systems فرستاده ميشه. كسايي كه نياز دارن به بنده مراجعه كنن
@Raminmousa
❤6👍3
The first channel on Telegram that offers exciting questions, answers, and tests in data science, artificial intelligence, machine learning, and programming languages.
#interviews #datascience #python
https://xn--r1a.website/DataScienceQ
#interviews #datascience #python
https://xn--r1a.website/DataScienceQ
👍5
[CVPR 2024] Diversity-aware Channel Pruning for StyleGAN Compression
🖥 Github: https://github.com/jiwoogit/dcp-gan
📕 Paper: https://arxiv.org/pdf/2403.13548v1.pdf
⭐️ Tasks: https://paperswithcode.com/task/image-generation
🔥Dataset: https://paperswithcode.com/dataset/ffhq
@Machine_learn
🖥 Github: https://github.com/jiwoogit/dcp-gan
📕 Paper: https://arxiv.org/pdf/2403.13548v1.pdf
⭐️ Tasks: https://paperswithcode.com/task/image-generation
🔥Dataset: https://paperswithcode.com/dataset/ffhq
@Machine_learn
❤3
🔥Grok-1 LLM .
Apache 2.0
▪ Model: https://dagshub.com/xai/grok-1
▪ Page: https://x.ai/blog/grok-os
▪ Code: https://github.com/xai-org/grok-1
▪ Hugging face:https://huggingface.co/xai-org/grok-1
@Machine_learn
Apache 2.0
▪ Model: https://dagshub.com/xai/grok-1
▪ Page: https://x.ai/blog/grok-os
▪ Code: https://github.com/xai-org/grok-1
▪ Hugging face:https://huggingface.co/xai-org/grok-1
@Machine_learn
❤3🔥2
This media is not supported in your browser
VIEW IN TELEGRAM
🦾 Supervision: reusable computer vision tools
▪Github:
▪Project
▪Colab
▪Supervision Cookbooks
@Machine_learn
pip install supervision▪Github:
▪Project
▪Colab
▪Supervision Cookbooks
@Machine_learn
👍8❤4🔥1
This media is not supported in your browser
VIEW IN TELEGRAM
🖼 One-Step Image Translation with Text-to-Image Models
CycleGAN-Turbo
▪Paper: https://arxiv.org/abs/2403.12036
▪Code: https://github.com/GaParmar/img2img-turbo
▪Demo: http://huggingface.co/spaces/gparmar/img2img-turbo-sketch
@Machine_learn
CycleGAN-Turbo
▪Paper: https://arxiv.org/abs/2403.12036
▪Code: https://github.com/GaParmar/img2img-turbo
▪Demo: http://huggingface.co/spaces/gparmar/img2img-turbo-sketch
@Machine_learn
❤6👍3🔥1
H-SAM
🖥 Github: https://github.com/cccccczh404/h-sam
📕 Paper: https://arxiv.org/pdf/2403.18271v1.pdf
🔥Dataset: https://paperswithcode.com/dataset/promise12
@Machine_learn
🖥 Github: https://github.com/cccccczh404/h-sam
📕 Paper: https://arxiv.org/pdf/2403.18271v1.pdf
🔥Dataset: https://paperswithcode.com/dataset/promise12
@Machine_learn
👍4❤1
📌skscope: Fast Sparse-Constraint Optimization
🖥 Github: https://github.com/abess-team/skscope
📕 Paper: https://arxiv.org/abs/2403.18540v1
🔥Dataset: skscope.readthedocs.io
Topics
@Machine_learn
🖥 Github: https://github.com/abess-team/skscope
📕 Paper: https://arxiv.org/abs/2403.18540v1
🔥Dataset: skscope.readthedocs.io
Topics
@Machine_learn
👍2
This media is not supported in your browser
VIEW IN TELEGRAM
🪴 SceneScript, a novel method for reconstructing environments and representing the layout of physical spaces
▪Paper
▪Project
▪Dataset
@Machine_learn
▪Paper
▪Project
▪Dataset
@Machine_learn
👍6
Long-Form Factuality in Large Language Models
🖥 Github: https://github.com/google-deepmind/long-form-factuality
📕 Paper: https://arxiv.org/pdf/2403.18802v1.pdf
🔥Dataset: https://paperswithcode.com/dataset/truthfulqa
@Machine_learn
🖥 Github: https://github.com/google-deepmind/long-form-factuality
📕 Paper: https://arxiv.org/pdf/2403.18802v1.pdf
🔥Dataset: https://paperswithcode.com/dataset/truthfulqa
@Machine_learn
👍1
Media is too big
VIEW IN TELEGRAM
⚡ StreamMultiDiffusion: Real-Time Interactive Generation with Region-Based Semantic Control
▪Сode: https://github.com/ironjr/StreamMultiDiffusion
▪Paper: https://arxiv.org/abs/2403.09055
@Machine_learn
▪Сode: https://github.com/ironjr/StreamMultiDiffusion
▪Paper: https://arxiv.org/abs/2403.09055
@Machine_learn
❤3
This media is not supported in your browser
VIEW IN TELEGRAM
🧬 Evolving New Foundation Models: Unleashing the Power of Automating Model Development
▪Blog: https://sakana.ai/evolutionary-model-merge/
▪Paper: https://arxiv.org/abs/2403.13187
@Machine_learn
▪Blog: https://sakana.ai/evolutionary-model-merge/
▪Paper: https://arxiv.org/abs/2403.13187
@Machine_learn
👍3❤1
AutoWebGLM: Bootstrap And Reinforce A Large Language Model-based Web Navigating Agent
🖥 Github: https://github.com/thudm/autowebglm
📕 Paper: https://arxiv.org/abs/2404.03648v1
🔥Dataset: https://paperswithcode.com/dataset/mind2web
@Machine_learn
🖥 Github: https://github.com/thudm/autowebglm
📕 Paper: https://arxiv.org/abs/2404.03648v1
🔥Dataset: https://paperswithcode.com/dataset/mind2web
@Machine_learn
👍3🔥1