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Found 5 papers, 0 papers with code
Catch & Carry: Reusable Neural Controllers for Vision-Guided Whole-Body Tasks
We address the longstanding challenge of producing flexible, realistic humanoid character controllers that can perform diverse whole-body tasks involving object interactions.
Neural probabilistic motor primitives for humanoid control
We focus on the problem of learning a single motor module that can flexibly express a range of behaviors for the control of high-dimensional physically simulated humanoids.
Hierarchical visuomotor control of humanoids
We aim to build complex humanoid agents that integrate perception, motor control, and memory.
Robust sketching for multiple square-root LASSO problems
Many learning tasks, such as cross-validation, parameter search, or leave-one-out analysis, involve multiple instances of similar problems, each instance sharing a large part of learning data with the others.
Dropout improves Recurrent Neural Networks for Handwriting Recognition
Recurrent neural networks (RNNs) with Long Short-Term memory cells currently hold the best known results in unconstrained handwriting recognition.
