ONNX-Net: Towards Universal Representations and Instant Performance Prediction for Neural Architectures
cs.LG, cs.AI, cs.CL
Submitted: 2025-10-06
Updated: 2026-08-26
Code: https://github.com/shiwenqin/ONNX-Net
Terminology
Sources
- Encodings for Prediction-based Neural Architecture Search
- SEKI: Self-Evolution and Knowledge Inspiration based Neural Architecture Search via Large Language Models
- Heterogeneous Graph Neural Architecture Search with GPT-4
- NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search
- LLM4GNAS: A Large Language Model Based Toolkit for Graph Neural Architecture Search
- LM-Searcher: Cross-domain Neural Architecture Search with LLMs via Unified Numerical Encoding
- LLM Performance Predictors are good initializers for Architecture Search
- Surprisingly Strong Performance Prediction with Neural Graph Features
- Hierarchical Representations for Efficient Architecture Search
- DARTS: Differentiable Architecture Search
- Transferrable Surrogates in Expressive Neural Architecture Search Spaces
- Surrogate NAS Benchmarks: Going Beyond the Limited Search Spaces of Tabular NAS Benchmarks
- Can GPT-4 Perform Neural Architecture Search?
- Neural Architecture Search with Reinforcement Learning
Related papers
- Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
- AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
- Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
- Convergence issues in Relational Concept Analysis based on AOC-posets
- Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
- Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks