Fast and Precise Learned Charged-Particle Trajectory Regression at the Large Hadron Collider
cs.LG
Submitted: 2026-09-26
Updated: 2026-09-26
Terminology
Sources
- ColliderML: The First Release of an OpenDataDetector High-Luminosity Physics Benchmark Dataset
- Were RNNs All We Needed?
- Attention Is All You Need
- Transformers for Charged Particle Track Reconstruction in High Energy Physics
- A Common Tracking Software Project
- Track fitting at the full LHC collision rate
- GPU-based Online Track Reconstruction for the ALICE TPC in Run 3 with Continuous Read-Out
- Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains
- Root Mean Square Layer Normalization
- On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
- E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials
- Generalisation in fully-connected neural networks for time series forecasting
- MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies
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