| DiNAS |
- Accuracy (Test)
- 94.37
- Accuracy (Val)
- 91.61
- Search time (s)
- 15.36
|
Multi-conditioned Graph Diffusion for Neural Architecture Search 2024-03-09 |
코드 1 |
| Shapley-NAS |
- Accuracy (Test)
- 94.37
- Accuracy (Val)
- 91.61
|
Shapley-NAS: Discovering Operation Contribution for Neural Architecture Search 2022-06-20 |
코드 1 |
| AG-Net |
- Accuracy (Test)
- 94.37
- Accuracy (Val)
- 91.61
|
Learning Where To Look -- Generative NAS is Surprisingly Efficient 2022-03-16 |
코드 1 |
| β-DARTS |
- Accuracy (Test)
- 94.36
- Accuracy (Val)
- 91.55
|
$β$-DARTS: Beta-Decay Regularization for Differentiable Architecture Search 2022-03-03 |
코드 1 |
| DrNAS |
- Accuracy (Test)
- 94.36
- Accuracy (Val)
- 91.55
|
DrNAS: Dirichlet Neural Architecture Search 2020-06-18 |
코드 1 |
| Λ-DARTS |
- Accuracy (Test)
- 94.36
- Accuracy (Val)
- 91.55
|
$Λ$-DARTS: Mitigating Performance Collapse by Harmonizing Operation Selection among Cells 2022-10-14 |
코드 1 |
| IS-DARTS |
- Accuracy (Test)
- 94.36
- Accuracy (Val)
- 91.55
|
IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate Importance 2023-12-19 |
코드 1 |
| CR-LSO |
- Accuracy (Test)
- 94.35
- Accuracy (Val)
- 91.54
|
CR-LSO: Convex Neural Architecture Optimization in the Latent Space of Graph Variational Autoencoder with Input Convex Neural Networks 2022-11-11 |
코드 1 |
| TNAS |
- Accuracy (Test)
- 94.35
|
When NAS Meets Trees: An Efficient Algorithm for Neural Architecture Search 2022-04-11 |
코드 1 |
| BaLeNAS-TF |
- Accuracy (Test)
- 94.33
- Accuracy (Val)
- 91.52
|
BaLeNAS: Differentiable Architecture Search via the Bayesian Learning Rule 2021-11-25 |
연결 없음 |
| NAR |
- Accuracy (Test)
- 94.33
- Accuracy (Val)
- 91.44
|
Generalized Global Ranking-Aware Neural Architecture Ranker for Efficient Image Classifier Search 2022-01-30 |
코드 1 |
| α-DARTS |
- Accuracy (Test)
- 94.3
- Accuracy (Val)
- 91.49
|
$α$ DARTS Once More: Enhancing Differentiable Architecture Search by Masked Image Modeling 2022-11-18 |
연결 없음 |
| RF-DARTS |
- Accuracy (Test)
- 94.27
- Accuracy (Val)
- 91.3
|
Differentiable Architecture Search with Random Features 2022-08-18 |
연결 없음 |
| arch2vec |
- Accuracy (Test)
- 94.18
- Accuracy (Val)
- 91.41
- Search time (s)
- 12000
|
Does Unsupervised Architecture Representation Learning Help Neural Architecture Search? 2020-06-12 |
코드 1 |
| GenNAS |
- Accuracy (Test)
- 94.18
- Accuracy (Val)
- -
- Search time (s)
- 1080
|
Generic Neural Architecture Search via Regression 2021-08-04 |
코드 1 · 코드 2 |
| GAEA DARTS (ERM) |
- Accuracy (Test)
- 94.1
|
Geometry-Aware Gradient Algorithms for Neural Architecture Search 2020-04-16 |
코드 1 |
| PRE-NAS |
- Accuracy (Test)
- 94.04
- Accuracy (Val)
- 91.37
|
PRE-NAS: Predictor-assisted Evolutionary Neural Architecture Search 2022-04-27 |
연결 없음 |
| CDARTS |
- Accuracy (Test)
- 94.02
- Accuracy (Val)
- 91.12
|
Cyclic Differentiable Architecture Search 2020-06-18 |
코드 1 · 코드 2 · 코드 3 |
| GAE |
- Accuracy (Test)
- 93.99
- Accuracy (Val)
- 91.26
|
Guided Evolutionary Neural Architecture Search With Efficient Performance Estimation 2022-07-22 |
연결 없음 |
| DU-DARTS |
- Accuracy (Test)
- 93.86
- Accuracy (Val)
- 91.21
|
DU-DARTS: Decreasing the Uncertainty of Differentiable Architecture Search 2021-11-23 |
코드 1 |
| DARTS- |
- Accuracy (Test)
- 93.80
- Accuracy (Val)
- 91.03
- Search time (s)
- 11520
|
DARTS-: Robustly Stepping out of Performance Collapse Without Indicators 2020-09-02 |
코드 1 |
| GDAS |
- Accuracy (Test)
- 93.61
- Accuracy (Val)
- 89.89
- Search time (s)
- 28926
|
Searching for A Robust Neural Architecture in Four GPU Hours 2019-10-10 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 |
| iDARTS |
- Accuracy (Test)
- 93.58
- Accuracy (Val)
- 89.86
|
iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients 2021-06-21 |
코드 1 |
| KNAS (k=40) |
- Accuracy (Test)
- 93.43
|
KNAS: Green Neural Architecture Search 2021-11-26 |
코드 1 |
| FairNAS |
- Accuracy (Test)
- 93.23
- Accuracy (Val)
- 90.07
- Search time (s)
- 9845
|
FairNAS: Rethinking Evaluation Fairness of Weight Sharing Neural Architecture Search 2019-07-03 |
코드 1 · 코드 2 |
| NAS-LID+RSPS |
- Accuracy (Test)
- 92.9
- Accuracy (Val)
- 89.74
|
NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension 2022-11-23 |
코드 1 |
| SNAS |
- Accuracy (Test)
- 92.77
- Accuracy (Val)
- 90.10
|
SNAS: Stochastic Neural Architecture Search 2018-12-24 |
코드 1 · 코드 2 |
| EPE-NAS (N=10) |
- Accuracy (Test)
- 92.63
- Accuracy (Val)
- 89.90
- Search time (s)
- 2.3
|
EPE-NAS: Efficient Performance Estimation Without Training for Neural Architecture Search 2021-02-16 |
코드 1 · 코드 2 |
| EPE-NAS (N=500) |
- Accuracy (Test)
- 92.27
- Accuracy (Val)
- 88.17
- Search time (s)
- 105.8
|
EPE-NAS: Efficient Performance Estimation Without Training for Neural Architecture Search 2021-02-16 |
코드 1 · 코드 2 |
| EPE-NAS (N=100) |
- Accuracy (Test)
- 91.59
- Accuracy (Val)
- 88.74
- Search time (s)
- 20.5
|
EPE-NAS: Efficient Performance Estimation Without Training for Neural Architecture Search 2021-02-16 |
코드 1 · 코드 2 |