Methods › Computer Vision › Feature Extractors › NEAT
Neural Attention Fields
NEAT
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
NEAT, or Neural Attention Fields, is a feature representation for end-to-end imitation learning models. NEAT is a continuous function which maps locations in Bird's Eye View (BEV) scene coordinates to waypoints and semantics, using intermediate attention maps to iteratively compress high-dimensional 2D image features into a compact representation. This allows the model to selectively attend to relevant regions in the input while ignoring information irrelevant to the driving task, effectively associating the images with the BEV representation. Furthermore, visualizing the attention maps for models with NEAT intermediate representations provides improved interpretability.
Papers archive 2025-07-28
25 shown of 25, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
-
NeuroPAL: Punctuated Anytime Learning with Neuroevolution for Macromanagement in Starcraft: Brood War 12 Jun 2025 · 0 repositories · arXiv:2506.10384
-
NEAT and HyperNEAT based Design for Soft Actuator Controllers 5 Jun 2025 · 0 repositories · arXiv:2506.04698
-
Near-Driven Autonomous Rover Navigation in Complex Environments: Extensions to Urban Search-and-Rescue and Industrial Inspection 11 Apr 2025 · 0 repositories · arXiv:2504.17794
-
TensorNEAT: A GPU-accelerated Library for NeuroEvolution of Augmenting Topologies 11 Apr 2025 · 1 repository · arXiv:2504.08339
-
State Estimation Using Particle Filtering in Adaptive Machine Learning Methods: Integrating Q-Learning and NEAT Algorithms with Noisy Radar Measurements 10 Apr 2025 · 0 repositories · arXiv:2504.07393
-
The Odyssey of the Fittest: Can Agents Survive and Still Be Good? 8 Feb 2025 · 1 repository · arXiv:2502.05442
-
NEAT Algorithm-based Stock Trading Strategy with Multiple Technical Indicators Resonance 11 Dec 2024 · 0 repositories · arXiv:2501.14736
-
PropNEAT -- Efficient GPU-Compatible Backpropagation over NeuroEvolutionary Augmenting Topology Networks 6 Nov 2024 · 0 repositories · arXiv:2411.03726
-
Negative-Prompt-driven Alignment for Generative Language Model 16 Oct 2024 · 0 repositories · arXiv:2410.12194
-
NEAT: Nonlinear Parameter-efficient Adaptation of Pre-trained Models 2 Oct 2024 · 0 repositories · arXiv:2410.01870
-
Tensorized NeuroEvolution of Augmenting Topologies for GPU Acceleration 2 Apr 2024 · 1 repository · arXiv:2404.01817
-
Inconsistency-Based Data-Centric Active Open-Set Annotation 10 Jan 2024 · 1 repository · arXiv:2401.04923
-
Neural Modelling of Dynamic Systems with Time Delays Based on an Adjusted NEAT Algorithm 21 Sep 2023 · 0 repositories · arXiv:2309.12148
-
Class Binarization to NeuroEvolution for Multiclass Classification 26 Aug 2023 · 1 repository · arXiv:2308.13876
-
A Look into Causal Effects under Entangled Treatment in Graphs: Investigating the Impact of Contact on MRSA Infection 17 Jul 2023 · 0 repositories · arXiv:2307.08237
-
NEAT: Distilling 3D Wireframes from Neural Attraction Fields 14 Jul 2023 · 1 repository · arXiv:2307.10206
-
EINCASM: Emergent Intelligence in Neural Cellular Automaton Slime Molds 22 May 2023 · 0 repositories · arXiv:2305.13425
-
Co-evolving morphology and control of soft robots using a single genome 22 Dec 2022 · 0 repositories · arXiv:2212.11517
-
ProSky: NEAT Meets NOMA-mmWave in the Sky of 6G 13 Oct 2022 · 1 repository · arXiv:2210.11406
-
Detecting Narrative Elements in Informational Text 6 Oct 2022 · 1 repository · arXiv:2210.03028
-
Playing a 2D Game Indefinitely using NEAT and Reinforcement Learning 28 Jul 2022 · 0 repositories · arXiv:2207.14140
-
Towards Understanding the Link Between Modularity and Performance in Neural Networks for Reinforcement Learning 13 May 2022 · 1 repository · arXiv:2205.06451
-
Hybrid Self-Attention NEAT: A novel evolutionary approach to improve the NEAT algorithm 7 Dec 2021 · 1 repository · arXiv:2112.03670
-
Adaptability of Improved NEAT in Variable Environments 22 Oct 2021 · 0 repositories · arXiv:2201.07977
-
NEAT: Neural Attention Fields for End-to-End Autonomous Driving 9 Sep 2021 · 1 repository · arXiv:2109.04456Syntology ran 0 of 2 samples · 2 unverified
Tasks archive 2025-07-28
20 shown of 37 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections