#nonlinearadaptivefiltering résultats de recherche

David J Klein

6 nov. 2013

#NonlinearAdaptiveFiltering #SequenceModeling #ManyFeatures #ManyClasses #ManyConditions #MultipleObjectClasses

Playing with texture filtering this morning! I think I do prefer the N64-style for Azaran 😋 A - 1080x1080 (HD source image) B - 32x32 point filter ("pixel"-style) C - 32x32 bilinear filter (Unity default) D - 32x32 3-sample bilinear filter (N64-style)

BenjiGameDev's tweet image. Playing with texture filtering this morning! I think I do prefer the N64-style for Azaran 😋

A - 1080x1080 (HD source image)
B - 32x32 point filter ("pixel"-style)
C - 32x32 bilinear filter (Unity default)
D - 32x32 3-sample bilinear filter (N64-style)

Aran Komatsuzaki

@arankomatsuzaki

11 avr. 2024

Scaling Laws for Data Filtering -- Data Curation cannot be Compute Agnostic Argues that data curation cannot be agnostic of the total compute that a model will be trained for repo: github.com/locuslab/scali… abs: arxiv.org/abs/2404.07177

arankomatsuzaki's tweet image. Scaling Laws for Data Filtering -- Data Curation cannot be Compute Agnostic

Argues that data curation cannot be agnostic of the total compute that a model will be trained for

repo: github.com/locuslab/scali…
abs: arxiv.org/abs/2404.07177

Hens

@HensDBD

11 févr. 2024

Today we are going to try to objectively measure how big the advantage gained from filters really is We will be switching between no filters casual filters and optimized ones with increased red saturation and try to see in how many situation they actually matter

HensDBD's tweet image. Today we are going to try to objectively measure how big the advantage gained from filters really is
We will be switching between no filters casual filters and optimized ones with increased red saturation and try to see in how many situation they actually matter

NeverSink

@NeverSinkDev

8 déc. 2023

Filters are live and updated! check out filterblade.xyz or the reddit thread for details reddit.com/r/pathofexile/… Also, now I can finally take care of my own POB! Image attached HAVE AN AWESOME AFFLICTION LEAGUE!

NeverSinkDev's tweet image. Filters are live and updated!

check out filterblade.xyz or the reddit thread for details reddit.com/r/pathofexile/…

Also, now I can finally take care of my own POB! Image attached

HAVE AN AWESOME AFFLICTION LEAGUE!

Tian Jin

@tjingrant

7 avr. 2023

We're dropping an experimental open source chrome extension to filter your feed with LLM according to an explicitly stated and user-editable preference. recalign.com . Code is here: github.com/recalign/RecAl… powered by @LangChainAI. 1/3

AK

@_akhaliq

2 janv. 2023

NIRVANA: Neural Implicit Representations of Videos with Adaptive Networks and Autoregressive Patch-wise Modeling abs: arxiv.org/abs/2212.14593

_akhaliq's tweet image. NIRVANA: Neural Implicit Representations of Videos with Adaptive Networks and Autoregressive Patch-wise Modeling
abs: arxiv.org/abs/2212.14593

Nasko

@Naskomusic

1 janv. 2023

N-COLOR IS HERE 👏👏👏 Isolate frequencies from a scale by filtering out off-key frequencies that don't belong to the selected key! Dynamic notch and peak filter system with a 220hz - 2.4khz processing area, Minor/Major scaling & mid-freq transient splitting!

나따🪿

@n_13_t

19 déc. 2022

Filter : トレジャー可愛くてごめん！ ทำฟิลเตอร์เทรเชอร์ขอโทษที่น่ารักมาฝากคับ! มีครบทุกเมมเยย ไปเล่นๆกันได้คับ ฝากทึเมเอ็นดูน้องด้วยน้าา🥺🤲🏻🤍 #ฟิลเตอร์ig 🔗 instagram.com/ar/68775482639…

n_13_t's tweet image. Filter : トレジャー可愛くてごめん！
ทำฟิลเตอร์เทรเชอร์ขอโทษที่น่ารักมาฝากคับ! มีครบทุกเมมเยย ไปเล่นๆกันได้คับ ฝากทึเมเอ็นดูน้องด้วยน้าา🥺🤲🏻🤍 #ฟิลเตอร์ig
🔗 instagram.com/ar/68775482639…

じゃがりこ【公式】

@jagarico_cp

19 mai 2022

\じゃがりこのARフィルターできたってよ🦒/ ★使い方(スマートフォンで操作下さい) ①下記URL or じゃがりこハニーバターチキン味のフタにある二次元コードを読み取って専用サイトにアクセス ②フィルターを選んで[つかってみる]をクリック ③Instagramでたくさん遊んでね❕ bddy.me/3sJ7g7A

$jagarico_cp's tweet image. \じゃがりこのARフィルターできたってよ🦒/ ★使い方(スマートフォンで操作下さい) ①下記URL or じゃがりこハニーバターチキン味のフタにある二次元コードを読み取って専用サイトにアクセス ②フィルターを選んで[つかってみる]をクリック ③Instagramでたくさん遊んでね❕ bddy.me/3sJ7g7A$

Jacob Andreas

@jacobandreas

6 mai 2022

New NAACL paper by @belindazli! We know lots about LM generalization at the example level, but comparatively little about LM "adaptability" at the task level. This paper uses a huge set of *randomly generated* tasks to explore the limits of LM adaptability. 🧵 w/ key findings:

jacobandreas's tweet image. New NAACL paper by @belindazli!

We know lots about LM generalization at the example level, but comparatively little about LM "adaptability" at the task level.

This paper uses a huge set of *randomly generated* tasks to explore the limits of LM adaptability. 🧵 w/ key findings:

anka⁷ 👨‍🚀🚀

@Hereforhealing7

26 août 2021

Sadly we know our filtering rate will be 50% atleast we need to have 12M unfiltered to beat that ...

Sara (R&R)

@SaraBangtan07

23 mai 2021

If we want to reduce our filter rate, it looks like there are 3 things we can do: - Join these official listening parties - Increase more unique listeners (ask everyone to listen to 🧈) - Keep on streaming smart ourselves

BTS_official

@bts_bighit

21 mai 2021

Come and join our listening parties with BTS members' favorite tracks! (*Spotify or Apple Music log-in required) 7일 동안의 리스닝 파티에 #BTSARMY 여러분을 초대합니다! (*스포티파이 또는 애플뮤직 로그인 필요) 💌 listeningparty.bts-butter.com #BTS #방탄소년단 #BTS_Butter

bts_bighit's tweet image. Come and join our listening parties with BTS members' favorite tracks!
(*Spotify or Apple Music log-in required)

7일 동안의 리스닝 파티에 #BTSARMY 여러분을 초대합니다!
(*스포티파이 또는 애플뮤직 로그인 필요)

💌 listeningparty.bts-butter.com
#BTS #방탄소년단 #BTS_Butter

Peyman Milanfar

@docmilanfar

19 mars 2021

Front-end resizers in deep networks are simple filters. They’re an afterthought — but they shouldn’t be Deep computer vision models can benefit greatly from replacing these fixed linear resizers with well-designed, learned, nonlinear resizers. A thread arxiv.org/abs/2103.09950

docmilanfar's tweet image. Front-end resizers in deep networks are simple filters. They’re an afterthought — but they shouldn’t be

Deep computer vision models can benefit greatly from replacing these fixed linear resizers with well-designed, learned, nonlinear resizers.

A thread

arxiv.org/abs/2103.09950

HLNLZ Updates

@hlnlzdaily

21 janv. 2021

📲| There’s a filter on Instagram called ‘Z Rescue’ by Zayn for NIL!

Zoubin Ghahramani

@ZoubinGhahrama1

11 déc. 2020

Fascinating use of probabilistic inference to build better optimizers from noisy gradients. Kalman filtering is a principled framework for adaptive step sizes and suppressing noise. Ironically works so well that it doesn’t explore enough for deep learning!

Ricky T. Q. Chen

@RickyTQChen

11 déc. 2020

We build a probabilistic gradient dynamics model, and explore inference as a sub-routine *for* stochastic optimization! Check out our contributed talk at …cant-believe-its-not-better.github.io (Dec 12) Paper: arxiv.org/abs/2011.04803 w/ @damichoi95 @lukas_balles @DavidDuvenaud @PhilippHennig5

akira

@AkiraTOSEI

8 oct. 2020

arxiv.org/abs/2007.08194 CNNのフィルターを１フィルターが1つのカテゴリを担当するような制約をかけることで、解釈性能を向上させる研究。最終層のフィルターに[0,1]の学習可能な行列をかけることにより各フィルターが1つのカテゴリしか使わないようにする。分類性能も損なわず可視化がより良くなる。

AkiraTOSEI's tweet image. arxiv.org/abs/2007.08194
CNNのフィルターを１フィルターが1つのカテゴリを担当するような制約をかけることで、解釈性能を向上させる研究。最終層のフィルターに[0,1]の学習可能な行列をかけることにより各フィルターが1つのカテゴリしか使わないようにする。分類性能も損なわず可視化がより良くなる。

tattaka

@tattaka_sun

27 nov. 2019

めちゃくちゃ簡単な実装でバッチサイズに左右されず精度上がってるのすごい Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep Neural Networks arxiv.org/abs/1911.09737

tattaka_sun's tweet image. めちゃくちゃ簡単な実装でバッチサイズに左右されず精度上がってるのすごい
Filter Response Normalization Layer: Eliminating Batch Dependence in the Training of Deep Neural Networks
arxiv.org/abs/1911.09737

DUNNA

@dunnadidit

8 avr. 2019

What are ND Filters? Why should you use them? How do you pick the best ND filter for your needs? In this video, we explore these wonderful tools and how they can be useful to you. Watch here -> youtu.be/8k1_mcP5Mf0 Featuring filters from @_PolarPro + @petermckinnon

dunnadidit's tweet image. What are ND Filters? Why should you use them? How do you pick the best ND filter for your needs? In this video, we explore these wonderful tools and how they can be useful to you.

Watch here -&gt; youtu.be/8k1_mcP5Mf0

Featuring filters from @_PolarPro + @petermckinnon

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