Video Prediction Transformers without Recurrence or Convolution

Yujin Tang, Lu Qi, Xiangtai Li, Chao Ma, Ming-Hsuan Yang

Action editor: Masha Itkina

https://openreview.net/forum?id=Afvhu9Id8m

#cnn #rnns #cnns

Uncovering the Computational Roles of Nonlinearity in Sequence Modeling Using Almost-Linear RNNs

Manuel Brenner, Georgia Koppe

Action editor: William Redman

https://openreview.net/forum?id=qI2Vt9P9rl

#rnns #recurrent #rnn

Fast weight programming and linear transformers: from machine learning to neurobiology

Kazuki Irie, Samuel J. Gershman

Action editor: Robert Legenstein

https://openreview.net/forum?id=TDG8EkNmQR

#rnns #synaptic #rnn

Measuring and Controlling Solution Degeneracy Across Task-Trained Recurrent Neural Networks - Kempner Institute Despite reaching equal performance success when trained on the same task, artificial neural networks can develop dramatically different internal solutions, much like different students solving the sam...

🤖📊 NEW in the Deeper Learning blog: @annhuang42.bsky.social & @kanakarajanphd.bsky.social break down their recent work examining how #RNNs solve the same task in different ways, and why that matters. Joint work with @satpreetsingh.bsky.social & @flavioh.bsky.social bit.ly/4kj4fVd #NeuroAI

Uncovering the Computational Roles of Nonlinearity in Sequence Modeling Using Almost-Linear RNNs

New #TMLR-Paper-with-Video:

Uncovering the Computational Roles of Nonlinearity in Sequence Modeling Using Almost-Linear RNNs

Manuel Brenner, Georgia Koppe

https://tmlr.infinite-conf.org/paper_pages/qI2Vt9P9rl

#rnns #recurrent #rnn

On the Expressiveness of Softmax Attention: A Recurrent Neural Network Perspective

New #TMLR-Paper-with-Video:

On the Expressiveness of Softmax Attention: A Recurrent Neural Network Perspective

Gabriel Mongaras, Eric C. Larson

https://tmlr.infinite-conf.org/paper_pages/PHcITOi3vV

#softmax #rnns #attention

New #Survey Certification:

Fast weight programming and linear transformers: from machine learning to neurobiology

Kazuki Irie, Samuel J. Gershman

https://openreview.net/forum?id=TDG8EkNmQR

#rnns #synaptic #rnn

On the Expressiveness of Softmax Attention: A Recurrent Neural Network Perspective

Gabriel Mongaras, Eric C. Larson

Action editor: Lingpeng Kong

https://openreview.net/forum?id=PHcITOi3vV

#softmax #rnns #attention

Recurrent Natural Policy Gradient for POMDPs

Semih Cayci, Atilla Eryilmaz

Action editor: Martha White

https://openreview.net/forum?id=6G01e0vgIf

#rnns #rnn #reinforcement

DRDT3: Diffusion-Refined Decision Test-Time Training Model

Xingshuai Huang, Di Wu, Benoit Boulet

Action editor: Mingming Gong

https://openreview.net/forum?id=I6zjLhIzgh

#rnns #rnn #drdt3

Rating: Teen And Up Audiences Archive Warning: No Archive Warnings Apply Category: Other Fandom: Blue Lock (Manga) Relationship: Itoshi Rin/Alexis Ness Characters: Itoshi Rin, Alexis Ness Additional Tags: Post-Canon, Angst, Angry Kissing, Itoshi Rin is Bad at Feelings, Itoshi Rin is Bad at Communicating, Alexis Ness Needs a Hug, Drabble Language: English Series: Part 2 of Kennn's Kiss Metre

‴𝐥𝐨𝐯𝐞𝐬𝐢𝐜𝐤 (𝐤𝐢𝐜𝐤𝐞𝐝) 𝐩𝐮𝐩𝐩𝐲‴

– #rnns #bllk
– Teen and Up
– drabble

🔗: archiveofourown.org/works/73279726

#KennnWrites

New #Reproducibility Certification:

DRDT3: Diffusion-Refined Decision Test-Time Training Model

Xingshuai Huang, Di Wu, Benoit Boulet

https://openreview.net/forum?id=I6zjLhIzgh

#rnns #rnn #drdt3

When one neuron becomes less excitable, its neighbors shift their tuning via lateral inhibition - reshaping the code while keeping downstream readouts stable.

#computationalneuroscience #RNNs #representationaldrift #neuraldynamics

State space models can express $n$-gram languages

Vinoth Nandakumar, Qiang Qu, Peng Mi, Tongliang Liu

Action editor: Razvan Pascanu

https://openreview.net/forum?id=QlBaDKb370

#rnns #gram #recurrent

The Human-AI Collaboration Imperative: Unlocking Complex Code Generation Potential with KNIME and… The importance of keeping the “human in the loop” when executing AI-driven, automated data flows

Can #AI reliably replace human expertise in #codegeneration? Stefano Puglia explores using #LLMs with #KNIME for adding an #Attention mechanisms to #RNNs. While powerful, AI's unpredictability demands #humanoversight for reliable outcomes. Don't miss it!

📌 #READ → medium.com/low-code-for...

Positional Encoding Helps Recurrent Neural Networks Handle a Large Vocabulary

Takashi Morita

Action editor: Alessandro Sperduti

https://openreview.net/forum?id=PtnwXd13SF

#rnns #positional #encode

Building Advanced Sentiment Models with Deep Learning: RNNs and LSTMs and Beyond A theoretical walkthrough with a hint to a visual implementation with KNIME

#SentimentAnalysis helps understand customers' feelings with a product or service. From rule-based methods to advanced #RNNs & #LSTMs, #DL drives accuracy in text analysis. Shanthababu Pandian shares benefits, challenges, and future insights. Check it out!

📌 #READ → medium.com/low-code-for...

The key to mastering #textclassification lies in understanding the power of #RNNs. These neural networks process and remember data, allowing for deeper insights and predictions.

RNNs offer a unique approach to managing large text datasets.
Want to dive deeper? 👉 https://buff.ly/3T5HFmK