Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI
๐ฅ Github: https://github.com/935963004/labram
๐ Paper: https://arxiv.org/abs/2405.18765v1
@Machine_learn
@Machine_learn
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Forwarded from Papers
ุณูุงู
ุฏูุณุชุงูู ูู ู
ูุงูู ุจุฑุงู ุงุฑุณุงู ุจู ฺูุฑูุงู ุฏุงุฑู ู
ู ุชููู ุจูุฏู ุฑู ุจู ุนููุงู ุฏุงูุฑ ุฏุฑ ุณู ฺูุฑูุงู ุฒูุฑ ู
ุนุฑูู ูููุฏ
1-Knowledge-Based system(https://www.sciencedirect.com/journal/knowledge-based-systems)
2-Machine learning with application(https://www.sciencedirect.com/journal/machine-learning-with-applications)
3-Ai(https://www.sciencedirect.com/journal/artificial-intelligence)
Name:Ramin Mousa
Email: Raminmousa@znu.ac.ir
ูู ฺููู ุฏูุณุชุงูู ูู ู ูุงูู ุจุฑุงู ุงุฑุณุงู ุฏุงุฑู ู ู ุชููู ูุจู ุงุฑุณุงู ุฌูุช ุจุฑุฑุณู ุจู ุจูุฏู ุงุฑุณุงู ููู ุชุง ูู ูพูุด ุฏุงูุฑู ุงูุฌุงู ุจุฏู .
@Raminmousa
@Paper4money
@Machine_learn
1-Knowledge-Based system(https://www.sciencedirect.com/journal/knowledge-based-systems)
2-Machine learning with application(https://www.sciencedirect.com/journal/machine-learning-with-applications)
3-Ai(https://www.sciencedirect.com/journal/artificial-intelligence)
Name:Ramin Mousa
Email: Raminmousa@znu.ac.ir
ูู ฺููู ุฏูุณุชุงูู ูู ู ูุงูู ุจุฑุงู ุงุฑุณุงู ุฏุงุฑู ู ู ุชููู ูุจู ุงุฑุณุงู ุฌูุช ุจุฑุฑุณู ุจู ุจูุฏู ุงุฑุณุงู ููู ุชุง ูู ูพูุด ุฏุงูุฑู ุงูุฌุงู ุจุฏู .
@Raminmousa
@Paper4money
@Machine_learn
โค1
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TensorIR: An Abstraction for Automatic Tensorized Program Optimization
Paper: https://arxiv.org/pdf/2207.04296v2.pdf
Codes: https://github.com/mlc-ai/web-llm - https://github.com/apache/tvm
โ
@Machine_learn
Paper: https://arxiv.org/pdf/2207.04296v2.pdf
Codes: https://github.com/mlc-ai/web-llm - https://github.com/apache/tvm
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# setting up a venv:
conda create -n depth-pro -y python=3.9
conda activate depth-pro
pip install -e .
# Download pretrained checkpoints:
source get_pretrained_models.sh
# Run the inference from CLI on a single image:
depth-pro-run -i ./data/example.jpg
# Running from python
from PIL import Image
import depth_pro
model, transform = depth_pro.create_model_and_transforms()
model.eval()
image, _, f_px = depth_pro.load_rgb(image_path)
image = transform(image)
prediction = model.infer(image, f_px=f_px)
depth = prediction["depth"] # Depth in [m].
focallength_px = prediction["focallength_px"] # Focal length in pixels.@Machine_learn
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Deep Learning and Computational Physics - Lecture Notes, University of South California
๐ book
@Machine_learn
๐ book
@Machine_learn
โค5
Forwarded from Github LLMs
Crawl 4 AI
Crawl4AI: Open-source LLM Friendly Web Crawler & Scrapper
Creator: UncleCode
Stars โญ๏ธ: 8.6k
Forked By: 627
https://github.com/unclecode/crawl4ai
โ
https://t.me/deep_learning_proj
Crawl4AI: Open-source LLM Friendly Web Crawler & Scrapper
Creator: UncleCode
Stars โญ๏ธ: 8.6k
Forked By: 627
https://github.com/unclecode/crawl4ai
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GitHub
GitHub - unclecode/crawl4ai: ๐๐ค Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper. Don't be shy, join here: https://disโฆ
๐๐ค Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper. Don't be shy, join here: https://discord.gg/jP8KfhDhyN - unclecode/crawl4ai
๐3
Generalizable and Animatable Gaussian Head Avatar
๐ฅ Github: https://github.com/xg-chu/gagavatar
๐ Paper: https://arxiv.org/abs/2410.07971v1
@Machine_learn
@Machine_learn
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ุจุง ุนุฑุถ ุณูุงู
ุฎููู ุงุฒ ุฏูุณุชุงู ุฏุฑ ุฑุงุจุทู ุจุง ุทุฑุงุญู ุตูุฑ ุชุง ุตุฏ ูพุฑฺูู ูุงู ุฏููพ ุงุฒ ุจูุฏู ุณูุงู ูพุฑุณูุฏู ุฏุงุฎู ูพู ุฒูุฑ ูฃูฆ ูพุฑฺูู ุฑู ุจุง ุฌุฒุฆูุงุช ุดุฑุญ ุฏุงุฏู
:
1-Deep Learning Basic
-01_Introduction
--01_How_TensorFlow_Works
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
ุฏูุณุชุงูู ูู ููุงุฒ ุจู ุงูู ูพุฑฺูู ูุง ุฏุงุฑู ู ูุชููู ุจุง ุจูุฏู ุฏุฑ ุงุฑุชุจุงุท ุจุงุดู.
@Raminmousa
@Machine_learn
1-Deep Learning Basic
-01_Introduction
--01_How_TensorFlow_Works
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
ุฏูุณุชุงูู ูู ููุงุฒ ุจู ุงูู ูพุฑฺูู ูุง ุฏุงุฑู ู ูุชููู ุจุง ุจูุฏู ุฏุฑ ุงุฑุชุจุงุท ุจุงุดู.
@Raminmousa
@Machine_learn
๐7โค1
Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts
๐ป Github: https://github.com/freedomintelligence/apollomoe
๐ Paper: https://arxiv.org/abs/2410.10626v1
๐ค Dataset: https://paperswithcode.com/dataset/mmlu
โ
@Machine_learn
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โค2๐1