Research map / Multi-agent systems and games / Human-AI and goal-conditioned
Gaussian Process Decentralized Data Fusion Meets Transfer Learning in Large-Scale Distributed Cooperative Perception
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use agent-centric support sets with lazy transfer learning instead of one shared support set | GP-DDF-ASS vs. GP-DDF · Indoor lighting quality | RMSE | Helped |
| Use agent-centric support sets with lazy transfer learning instead of one shared support set | GP-DDF-ASS vs. GP-DDF · Indian Ocean sea surface temperature | RMSE | Helped |
| Use agent-centric support sets with lazy transfer learning instead of one shared support set | GP-DDF$^+$-ASS vs. GP-DDF$^+$ · Indoor lighting quality | RMSE | Helped |
| Use agent-centric support sets with lazy transfer learning instead of one shared support set | GP-DDF$^+$-ASS vs. GP-DDF$^+$ · Indian Ocean sea surface temperature | RMSE | Helped |
| Transfer information between different local support sets | GP-DDF-ASS · Simulated spatial phenomena | RMSE | Helped |
| Use a single support set distributed over the full domain rather than local support sets | GP-DDF vs. local PITCs · Simulated spatial phenomena | RMSE | Hurt |
| Use local support sets without transferring information across local areas | Local PITCs vs. GP-DDF-ASS · Simulated spatial phenomena | RMSE | Hurt |
| Use GP-DDF-ASS instead of local GPs | GP-DDF-ASS · Indoor lighting quality and Indian Ocean sea surface temperature | RMSE | Mixed |
| Add local-data exploitation to GP-DDF-ASS (ablation) | GP-DDF$^+$-ASS vs. GP-DDF-ASS · Indoor lighting quality and Indian Ocean sea surface temperature | RMSE | Helped |
| Add local-data exploitation to GP-DDF-ASS (ablation) | GP-DDF$^+$-ASS vs. GP-DDF-ASS · Indoor lighting quality and Indian Ocean sea surface temperature | time | Hurt |
| Use transfer learning across local areas | GP-DDF-ASS vs. local PITCs · Simulated spatial phenomena with intermediate length-scales | RMSE | Helped |
| Use transfer learning across local areas | GP-DDF-ASS vs. local PITCs · Simulated spatial phenomena with very small or very large length-scales | RMSE reduction over local PITCs | No clear effect |
Closest papers by meaning
- Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems (AAAI 2019 · similarity 0.87)
- CooperTrim: Adaptive Data Selection for Uncertainty-Aware Cooperative Perception (ICLR 2026 · similarity 0.85)
- Unsupervised Multi-agent and Single-agent Perception from Cooperative Views (CVPR 2026 · similarity 0.85)
- Reinventing Multi-Agent Collaboration through Gaussian-Image Synergy in Diffusion Policies (NeurIPS 2025 · similarity 0.84)
- An Extensible Framework for Open Heterogeneous Collaborative Perception (ICLR 2024 · similarity 0.83)
- CoPEFT: Fast Adaptation Framework for Multi-Agent Collaborative Perception with Parameter-Efficient Fine-Tuning (AAAI 2025 · similarity 0.82)
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