Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2407.17356
Cited By
Gradient-based inference of abstract task representations for generalization in neural networks
24 July 2024
Ali Hummos
Felipe del-Rio
Brabeeba Mien Wang
Julio Hurtado
Cristian B. Calderon
G. Yang
Re-assign community
ArXiv
PDF
HTML
Papers citing
"Gradient-based inference of abstract task representations for generalization in neural networks"
5 / 5 papers shown
Title
Flexible task abstractions emerge in linear networks with fast and bounded units
Kai Sandbrink
Jan P. Bauer
A. Proca
Andrew M. Saxe
Christopher Summerfield
Ali Hummos
58
2
0
17 Jan 2025
Meta-Dynamical State Space Models for Integrative Neural Data Analysis
Ayesha Vermani
Josue Nassar
Hyungju Jeon
Matthew Dowling
Il Memming Park
29
1
0
07 Oct 2024
The Power of Scale for Parameter-Efficient Prompt Tuning
Brian Lester
Rami Al-Rfou
Noah Constant
VPVLM
280
3,843
0
18 Apr 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,660
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,134
0
06 Jun 2015
1