mlsanityData to 7 Oct 2026

A Generic Graph-based Neural Architecture Encoding Scheme for Predictor-based NAS

arXiv 2004.01899 ↗First posted 4 Apr 2020cs.LG cs.NE stat.MLcited by 53

Not on the map. Why?

Abstract (arXiv)

This work proposes a novel Graph-based neural ArchiTecture Encoding Scheme, a.k.a. GATES, to improve the predictor-based neural architecture search. Specifically, different from existing graph-based schemes, GATES models the operations as the transformation of the propagating information, which mimics the actual data processing of neural architecture. GATES is a more reasonable modeling of the neural architectures, and can encode architectures from both the "operation on node" and "operation on edge" cell search spaces consistently. Experimental results on various search spaces confirm GATES's effectiveness in improving the performance predictor. Furthermore, equipped with the improved performance predictor, the sample efficiency of the predictor-based neural architecture search (NAS) flow is boosted. Codes are available at https://github.com/walkerning/aw_nas.

Key facts. Cited by 53 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Apr 2020.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 14; 2022: 9; 2023: 10; 2024: 6; 2025: 10; 2026: 4.

53 papers.

Sort:

By area:

  1. 2023Neural Architecture Search: Insights from 1000 Paperscited by 136
  2. 2021How Powerful are Performance Predictors in Neural Architecture Search?cited by 88
  3. 2023OMS-DPM: Optimizing the Model Schedule for Diffusion Probabilistic Modelscited by 44
  4. 2021Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learningcited by 30
  5. 2021Stronger NAS with Weaker Predictorscited by 28
  6. 2021CATE: Computation-aware Neural Architecture Encoding with Transformerscited by 21
  7. 2021GradSign: Model Performance Inference with Theoretical Insightscited by 18
  8. 2023DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion Modelscited by 15
  9. 2023A Unified Sampling Framework for Solver Searching of Diffusion Probabilistic Modelscited by 14
  10. 2021RankNAS: Efficient Neural Architecture Search by Pairwise Rankingcited by 12
  11. 2022A Survey on Computationally Efficient Neural Architecture Searchcited by 12
  12. 2022NAR-Former: Neural Architecture Representation Learning towards Holistic Attributes Predictioncited by 12
38 more
  1. 2021FLASH: Fast Neural Architecture Search with Hardware Optimizationcited by 11
  2. 2023AnalogNAS: A Neural Network Design Framework for Accurate Inference with Analog In-Memory Computingcited by 10
  3. 2025Regression Language Models for Codecited by 10
  4. 2021RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halvingcited by 9
  5. 2022Arch-Graph: Acyclic Architecture Relation Predictor for Task-Transferable Neural Architecture Searchcited by 9
  6. 2024FlowerFormer: Empowering Neural Architecture Encoding using a Flow-aware Graph Transformercited by 9
  7. 2023GP-NAS-ensemble: a model for NAS Performance Predictioncited by 7
  8. 2023NAR-Former V2: Rethinking Transformer for Universal Neural Network Representation Learningcited by 6
  9. 2024Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Bettercited by 6
  10. 20213D-ANAS: 3D Asymmetric Neural Architecture Search for Fast Hyperspectral Image Classificationcited by 5
  11. 2021Graph-based Neural Architecture Search with Operation Embeddingscited by 5
  12. 2022CLOSE: Curriculum Learning On the Sharing Extent Towards Better One-shot NAScited by 5
  13. 2022CODEBench: A Neural Architecture and Hardware Accelerator Co-Design Frameworkcited by 5
  14. 2024ParZC: Parametric Zero-Cost Proxies for Efficient NAScited by 5
  15. 2024Architecture-Aware Learning Curve Extrapolation via Graph Ordinary Differential Equationcited by 5
  16. 2024CAP: A Context-Aware Neural Predictor for NAScited by 4
  17. 2021Accelerating Multi-Objective Neural Architecture Search by Random-Weight Evaluationcited by 3
  18. 2022Bi-fidelity Evolutionary Multiobjective Search for Adversarially Robust Deep Neural Architecturescited by 3
  19. 2022Visual Analysis of Neural Architecture Spaces for Summarizing Design Principlescited by 3
  20. 2023Dynamic Ensemble of Low-fidelity Experts: Mitigating NAS "Cold-Start"cited by 3
  21. 2023DCLP: Neural Architecture Predictor with Curriculum Contrastive Learningcited by 3
  22. 2021A Data-driven Approach to Neural Architecture Search Initializationcited by 2
  23. 2022CR-LSO: Convex Neural Architecture Optimization in the Latent Space of Graph Variational Autoencoder with Input Convex Neural Networkscited by 2
  24. 2025CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictorcited by 2
  25. 2025NN-Former: Rethinking Graph Structure in Neural Architecture Representationcited by 2
  26. 2026GraphIR: Architecture-Level Search States for LLM-Guided Neural Architecture Evolutioncited by 2
  27. 2021Cascade Bagging for Accuracy Prediction with Few Training Samplescited by 1
  28. 2024GRASP-GCN: Graph-Shape Prioritization for Neural Architecture Search under Distribution Shiftscited by 1
  29. 2025GATES: Cost-aware Dynamic Workflow Scheduling via Graph Attention Networks and Evolution Strategycited by 1
  30. 2025Loss Functions for Predictor-based Neural Architecture Searchcited by 1
  31. 2025Zero-Shot Neural Architecture Search with Weighted Response Correlationcited by 1
  32. 2025ESM: A Framework for Building Effective Surrogate Models for Hardware-Aware Neural Architecture Searchcited by 1
  33. 2025Learning to Flow from Generative Pretext Tasks for Neural Architecture Encodingcited by 1
  34. 2021Pretraining Neural Architecture Search Controllers with Locality-based Self-Supervised Learningcited by 0
  35. 2022WPNAS: Neural Architecture Search by jointly using Weight Sharing and Predictorcited by 0
  36. 2023Efficacy of Neural Prediction-Based Zero-Shot NAScited by 0
  37. 2025Neural Architecture Search by Learning a Hierarchical Search Spacecited by 0
  38. 2025Language Embedding Meets Dynamic Graph: A New Exploration for Neural Architecture Representation Learningcited by 0

50 most cited of 53 All 53 (JSON)