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. 2011.06006
  4. Cited By
Towards NNGP-guided Neural Architecture Search

Towards NNGP-guided Neural Architecture Search

11 November 2020
Daniel S. Park
Jaehoon Lee
Daiyi Peng
Yuan Cao
Jascha Narain Sohl-Dickstein
    BDL
ArXivPDFHTML

Papers citing "Towards NNGP-guided Neural Architecture Search"

9 / 9 papers shown
Title
How Feature Learning Can Improve Neural Scaling Laws
How Feature Learning Can Improve Neural Scaling Laws
Blake Bordelon
Alexander B. Atanasov
C. Pehlevan
57
12
0
26 Sep 2024
Rethink DARTS Search Space and Renovate a New Benchmark
Rethink DARTS Search Space and Renovate a New Benchmark
Jiuling Zhang
Zhiming Ding
35
1
0
12 Jun 2023
Fast Finite Width Neural Tangent Kernel
Fast Finite Width Neural Tangent Kernel
Roman Novak
Jascha Narain Sohl-Dickstein
S. Schoenholz
AAML
22
53
0
17 Jun 2022
Deep Active Learning by Leveraging Training Dynamics
Deep Active Learning by Leveraging Training Dynamics
Haonan Wang
Wei Huang
Ziwei Wu
A. Margenot
Hanghang Tong
Jingrui He
AI4CE
27
33
0
16 Oct 2021
NASI: Label- and Data-agnostic Neural Architecture Search at
  Initialization
NASI: Label- and Data-agnostic Neural Architecture Search at Initialization
Yao Shu
Shaofeng Cai
Zhongxiang Dai
Beng Chin Ooi
K. H. Low
22
43
0
02 Sep 2021
Dataset Distillation with Infinitely Wide Convolutional Networks
Dataset Distillation with Infinitely Wide Convolutional Networks
Timothy Nguyen
Roman Novak
Lechao Xiao
Jaehoon Lee
DD
49
229
0
27 Jul 2021
Generalization Guarantees for Neural Architecture Search with
  Train-Validation Split
Generalization Guarantees for Neural Architecture Search with Train-Validation Split
Samet Oymak
Mingchen Li
Mahdi Soltanolkotabi
AI4CE
OOD
36
13
0
29 Apr 2021
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train
  10,000-Layer Vanilla Convolutional Neural Networks
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks
Lechao Xiao
Yasaman Bahri
Jascha Narain Sohl-Dickstein
S. Schoenholz
Jeffrey Pennington
227
348
0
14 Jun 2018
Neural Architecture Search with Reinforcement Learning
Neural Architecture Search with Reinforcement Learning
Barret Zoph
Quoc V. Le
271
5,329
0
05 Nov 2016
1