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Create: 2024-11-07 Update: 2025-07-06 09:52:27

کار دیگه ای که شباهت هایی به مقاله قبلی داره کار آقای رامین حسنی از MIT هست.

عنوان مقاله Liquid Time Constant Networks هست. این مدل در واقع نوعی شبکه عصبی پویا و انعطاف ‌پذیره که برای پردازش اطلاعات در زمان و تصمیم ‌گیری در شرایط پیچیده با الهام از ساختارهای عصبی موجودات زنده طراحی شده.

توی شبکه‌ های سنتی، اتصالات و زمان ‌بندی واحدهای عصبی ثابت هستن، اما در LTCNs زمان‌ بندی یا ثابت زمانی نورون‌ ها به صورت پویا تغییر میکنن و به همین دلیل به اون "liquid" گفته میشه.

ویژگی دینامیک LTCN به شبکه اجازه میده به محیط‌ های پویا و شرایط متغیر واکنش بهتری نشون بده.

این شبکه‌ ها با تنظیم پیوسته ثابت‌های زمانی نورون‌ ها، میتونن با داده‌های ورودی سازگار بشن و پاسخ ‌های انعطاف ‌پذیرتری رو ارایه بدن.

به صورت فنی تر بایستی عرض کنم که LTCN‌ها در واقع نوعی شبکه عصبی بازگشتی هستن که هر نورون از یه معادله‌ خاص پیروی میکنه.

این معادلات به شبکه اجازه میدن تا رفتار نورون ‌ها رو به عنوان یک تابع از ورودی‌ ها و شرایط محیطی تغییر بدن.

نورون ‌ها در LTCN‌ها دارای ثابت‌های زمانی متغیر هستن که بسته به شرایط، سرعت یا کندی تغییرات اونها رو تنظیم می‌کنه.

این تغییرات در «ثابت‌های زمانی» باعث میشه که شبکه در مواجهه با ورودی‌ های مختلف، پاسخ‌ های متنوعی داشته باشه.

البته توضیحات کامل رو خود آقای حسنی توی ویدئوی زیر به صورت کامل شرح میدن:

ادامه دارد ...

https://youtu.be/IlliqYiRhMU?si=nstNmmU7Nwo06KSJ&t=1971

Tensorflow(@CVision)

اگه این نظریه صحیح باشه، احتمالش زیاده که بشه همچین سیستمی رو توی حوزه هوش مصنوعی پیاده کرد. البته این کار توی الگوریتم یادگیری تقویتی به اسم SMiRL انجام شده و نسبتا موفقیت ‌آمیز بوده. عنوان مقاله یادگیری تقویتی مبتنی بر کمینه سازی شگفتی در محیط ‌های ناپایدار…

YouTube

Liquid Neural Networks

Ramin Hasani, MIT - intro by Daniela Rus, MIT

Abstract: In this talk, we will discuss the nuts and bolts of the novel continuous-time neural network models: Liquid Time-Constant (LTC) Networks. Instead of declaring a learning system's dynamics by implicit…

hottg.com/cvision/3801

2.3K viewsAlister ☄️, edited Nov 7, 2024 at 18:28

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کار دیگه ای که شباهت هایی به مقاله قبلی داره کار آقای رامین حسنی از MIT هست.

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