ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2006.07123
  4. Cited By
Kernelized information bottleneck leads to biologically plausible
  3-factor Hebbian learning in deep networks

Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks

12 June 2020
Roman Pogodin
P. Latham
ArXivPDFHTML

Papers citing "Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks"

5 / 5 papers shown
Title
Short-Term Plasticity Neurons Learning to Learn and Forget
Short-Term Plasticity Neurons Learning to Learn and Forget
Hector Garcia Rodriguez
Qinghai Guo
Timoleon Moraitis
13
12
0
28 Jun 2022
Deep Layer-wise Networks Have Closed-Form Weights
Chieh-Tsai Wu
A. Masoomi
A. Gretton
Jennifer Dy
29
3
0
01 Feb 2022
SoftHebb: Bayesian Inference in Unsupervised Hebbian Soft
  Winner-Take-All Networks
SoftHebb: Bayesian Inference in Unsupervised Hebbian Soft Winner-Take-All Networks
Timoleon Moraitis
Dmitry Toichkin
Adrien Journé
Yansong Chua
Qinghai Guo
AAML
BDL
68
28
0
12 Jul 2021
Towards Biologically Plausible Convolutional Networks
Towards Biologically Plausible Convolutional Networks
Roman Pogodin
Yash Mehta
Timothy Lillicrap
P. Latham
26
22
0
22 Jun 2021
Training Deep Architectures Without End-to-End Backpropagation: A Survey
  on the Provably Optimal Methods
Training Deep Architectures Without End-to-End Backpropagation: A Survey on the Provably Optimal Methods
Shiyu Duan
José C. Príncipe
MQ
20
3
0
09 Jan 2021
1