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Found 5 papers, 2 papers with code
Robust Multi-Modal Density Estimation
Development of multi-modal, probabilistic prediction models has lead to a need for comprehensive evaluation metrics.
Rethinking Sharpness-Aware Minimization as Variational Inference
Sharpness-aware minimization (SAM) aims to improve the generalisation of gradient-based learning by seeking out flat minima.
Depth Without the Magic: Inductive Bias of Natural Gradient Descent
In gradient descent, changing how we parametrize the model can lead to drastically different optimization trajectories, giving rise to a surprising range of meaningful inductive biases: identifying sparse classifiers or reconstructing low-rank matrices without explicit regularization.
Learning to Pick at Non-Zero-Velocity from Interactive Demonstrations
This work investigates how the intricate task of a continuous pick & place (P&P) motion may be learned from humans based on demonstrations and corrections.
ILoSA: Interactive Learning of Stiffness and Attractors
Teaching robots how to apply forces according to our preferences is still an open challenge that has to be tackled from multiple engineering perspectives.
