Residual connections enforce artificial smoothing across topological breaks in control manifolds — a structural mismatch for robotics. Investigating whether Plain (non-residual) DNNs trained via the Muon optimizer can preserve sharp decision boundaries while circumventing the gradient vanishing constraints that make plain networks hard to train with SGD or Adam.
An intelligence platform that translates global volatility into contextualized risk signals, minimizing the latency between external disruptions and operational awareness.
A primer on the HHL algorithm — how quantum computers can invert sparse linear systems in polylogarithmic time, an exponential leap over classical methods.