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Course Correcting Koopman Representations
Koopman representations aim to learn features of nonlinear dynamical systems (NLDS) which lead to linear dynamics in the latent space.
Continuous-Time Meta-Learning with Forward Mode Differentiation
Drawing inspiration from gradient-based meta-learning methods with infinitely small gradient steps, we introduce Continuous-Time Meta-Learning (COMLN), a meta-learning algorithm where adaptation follows the dynamics of a gradient vector field.
Simple Video Generation using Neural ODEs
Despite having been studied to a great extent, the task of conditional generation of sequences of frames, or videos, remains extremely challenging.
TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning?
We investigate whether Jacobi preconditioning, accounting for the bootstrap term in temporal difference (TD) learning, can help boost performance of adaptive optimizers.
Recurrent Semi-supervised Classification and Constrained Adversarial Generation with Motion Capture Data
We find that using such constraints allow to stabilize the training of recurrent adversarial architectures for animation generation.
