SMR uses multi-channel map-encoded reinforcement learning to achieve roughly 10% better time utilization than greedy baselines for single-dish radio telescope scheduling.
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UNVERDICTED 3representative citing papers
Boundary conditions in GR for axially symmetric rotating dust can reproduce effects usually attributed to dark matter.
Different coordinate frames for static axisymmetric vacuum spacetimes produce different effective potentials and rotation curves for low-velocity local observers.
citing papers explorer
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SMR: Scheduler with Multi-Channel Map-Encoded Reinforcement Learning for Radio Telescopes
SMR uses multi-channel map-encoded reinforcement learning to achieve roughly 10% better time utilization than greedy baselines for single-dish radio telescope scheduling.
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Non-trivial boundary conditions in general-relativistic models
Boundary conditions in GR for axially symmetric rotating dust can reproduce effects usually attributed to dark matter.
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On Coordinate Frames in Axisymmetric Static Vacuum Spacetimes and Implications for Observations
Different coordinate frames for static axisymmetric vacuum spacetimes produce different effective potentials and rotation curves for low-velocity local observers.