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Lorentz Group Equivariant Neural Network for Particle Physics
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Lorentz-equivariant LGN instead of ParticleNet | Top tagging classifier · Top tagging | accuracy: 0.938 -> 0.929 | Hurt |
| Use Lorentz-equivariant LGN instead of ParticleNet | Top tagging classifier · Top tagging | AUC: 0.985 -> 0.964 | Hurt |
| Use Lorentz-equivariant LGN instead of ParticleNet | Top tagging classifier · Top tagging | 1/ε_B at ε_S=0.3: 1298 ± 46 -> 435 ± 95 | Hurt |
| Use Lorentz-equivariant LGN instead of ParticleNet | Top tagging classifier · Top tagging | trainable parameters: 498k -> 4.5k | Helped |
Closest papers by meaning
- Lorentz Local Canonicalization: How to make any Network Lorentz-Equivariant (NeurIPS 2025 · similarity 0.89)
- Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics (NeurIPS 2024 · similarity 0.89)
- Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups (ICLR 2025 · similarity 0.87)
- Equivariant Neural Tangent Kernels (ICML 2025 · similarity 0.87)
- Clifford-Steerable Convolutional Neural Networks (ICML 2024 · similarity 0.86)
- Lie Group Decompositions for Equivariant Neural Networks (ICLR 2024 · similarity 0.86)
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