Accurate prediction of pseudoknotted nucleic acid secondary structure is an important computational challenge. Prediction algorithms based on dynamic programming aim to find a st...
We present parallel algorithms for processing, extracting and rendering adaptively sampled regular terrain datasets represented as a multiresolution model defined by a super-squa...
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
Developable surfaces are modelled with pieces of right circular cones. These cone spline surfaces are well-suited for applications: They possess degree two parametric and implicit...
Agents engaged in noncooperative interaction may seek to achieve a Nash equilibrium; this requires that agents be aware of others’ rewards. Misinformation about rewards leads to...