Weighted Deep Neural Network Ensemble Approach for
Multi-Domain Sentiment Analysis Author: @Raminmousa Doi:https://dx.doi.org/10.22105/jarie.2021.288364.1332 cite: Mousa, Ramin, et al. "Weighted Deep Neural Network Ensemble Approach for Multi-Domain Sentiment Analysis." Journal of Applied Research on Industrial Engineering (2021). link: https://www.researchgate.net/publication/360645256_Weighted_Deep_Neural_Network_Ensemble_Approach_for_Multi-Domain_Sentiment_Analysis @Machine_learn

ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer

Github: https://github.com/locuslab/convmixer

Paper: https://arxiv.org/pdf/2201.09792v1.pdf

@Machine_learn

📹 VRT: A Video Restoration Transformer

Github: https://github.com/jingyunliang/vrt

Paper: https://arxiv.org/abs/2201.12288

Dataset: https://paperswithcode.com/dataset/gopro

@Machine_learn

📝 Automated Crossword Solving

Pretrained models, precomputed FAISS embeddings, and a crossword clue-answer dataset.

Github: https://github.com/albertkx/berkeley-crossword-solver

Paper: https://arxiv.org/abs/2205.09665v1

Dataset: https://www.xwordinfo.com/JSON/

@Machine_learn

[CVPR 2022] PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination under Self-supervision (Oral)

https://github.com/Garfield-kh/PoseTriplet

@Machine_lean

📍 Perturbation Augmentation for Fairer NLP

Responsible NLP projects from Meta AI.

Github: https://github.com/facebookresearch/responsiblenlp

Paper: https://arxiv.org/abs/2205.12586v1

Dataset: https://paperswithcode.com/dataset/glue

@Machine_learn

Randomized Deep Learning Methods for Clinical Trial Enrichment and Design in Alzheimer’s Disease #Chapter15
@Machine_learn

Deep Networks and Mutual Information Maximization for Cross-Modal Medical Image Synthesis #Chapter16
@Machine_learn

Natural Language Processing for Large-Scale Medical Image Analysis Using Deep Learning
#Chapter17
@Machine_learn

🦠 MaSIF- Molecular Surface Interaction Fingerprints: Geometric deep learning to decipher patterns in protein molecular surfaces.

MaSIF is a proof-of-concept method to decipher patterns in protein surfaces important for specific biomolecular interactions.

Github: https://github.com/LPDI-EPFL/masif

Paper: https://www.nature.com/articles/s41592-019-0666-6

Data: https://github.com/LPDI-EPFL/masif#MaSIF-data-preparation

@Machine_learn

🪄 Investigating the Role of Image Retrieval for Visual Localization -- An exhaustive benchmark.

Github: https://github.com/naver/kapture-localization

Paper: https://arxiv.org/abs/2205.15761v1

Data: https://paperswithcode.com/dataset/inloc

@Machine_learn

PROGRAMMING FOR PROBLEM SOLVING DIGITAL NOTES

📖 Book

@machine_learn

اخرين تخفيف تا فردا شب #٥٠٪؜

⛩ XBound-Former: Toward Cross-scale Boundary Modeling in Transformers

Github: https://github.com/naiyugao/panopticdepth

Paper: https://arxiv.org/abs/2206.00806v1

Dataset: https://paperswithcode.com/dataset/kvasir-seg

@Machine_learn

Chinese students ride bicycles to build their own drones.

This bike is the latest artificial intelligence technology that allows it to learn "like a human". Able to identify and track. () (() () (

This operation requires 100 accounts per second! The speed and efficiency of artificial intelligence is so high that these calculations can be performed with high accuracy. And make the bike smart enough to act like a human and make decisions.

+ In short, I can tell you that you can say with this bike, go get two loaves of bread and come back.‌ It will do it for you.

https://www.tg-me.com/Machine_learn

با عرض سلام موضوعات پيشنهادي تز
برای دوستانی که نیاز دارن در ادامه اورده شده است.


master thesis

پيش بيني بار كوتاه مدت با استفاده از رويكردهاي يادگيري تركيبي

طبقه بندي رضايت مشتريان بانكي و موسسات اعتباري با استفاده از رويكردهاي بازگشتي

طبقه بندي اخبار جعل با استفاده از رويكرد تنسور سه بعدي و bert

پيشبيني قيمت سهام با استفاده از اطلاعات تويتر و ماركت

پيش بيني قيمت crypto با استفاده از اطلاعات hashrate

phd thesis

بهبود رویکردهای یادگیری عمیق بر روی اخبار جعل و شایعات

بهبود رویکرد های یادگیری عمیق ترکیبی جهت دستیابی به پورتوفولی بهینه

بهبود رویکردهای ترکیبی یادگیری عمیق برای طبقه بندی crypto با استفاده از اطلاعات hashrate

ارائه رویکردهای مبتنی بر وزن دهی غیر تصادفی در یادگیری عمیق

بهبود یادگیری انتقالی در سری زمانی

ارائه مدل های انتقالی برای طبقه بندی های سری زمانی

جهت مشاوره موضوعات می تونین با بنده در ارتباط باشین


@Raminmousa

🎆 Optimizing Relevance Maps of Vision Transformers Improves Robustness

This code allows to finetune the explainability maps of Vision Transformers to enhance robustness.

Github: https://github.com/hila-chefer/robustvit

Colab: https://colab.research.google.com/github/hila-chefer/RobustViT/blob/master/RobustViT.ipynb

Paper: https://arxiv.org/abs/2206.01161

Dataset: https://github.com/UnsupervisedSemanticSegmentation/ImageNet-S

@Machine_learn

Invertible Neural Networks for Graph Prediction

Github: https://github.com/hamrel-cxu/invertible-graph-neural-network-ignn

Paper: https://arxiv.org/abs/2206.01163v1

@Machine_learn

Quantum Advantage in Learning from Experiments


http://ai.googleblog.com/2022/06/quantum-advantage-in-learning-from.html

@Machine_learn