TimewarpVAE: Simultaneous Time-Warping and Representation Learning of Trajectories

1 code implementation • 24 Oct 2023 • Travers Rhodes, Daniel D. Lee

Human demonstrations of trajectories are an important source of training data for many machine learning problems.

Dynamic Time Warping Representation Learning

Learning from Demonstration using a Curvature Regularized Variational Auto-Encoder (CurvVAE)

1 code implementation • IEEE International Conference on Intelligent Robots and Systems (IROS) 2022 • Travers Rhodes, Tapomayukh Bhattacharjee, and Daniel D. Lee

Learning intricate manipulation skills from human demonstrations requires good sample efficiency.

Local Disentanglement in Variational Auto-Encoders Using Jacobian $L_1$ Regularization

1 code implementation • NeurIPS 2021 • Travers Rhodes, Daniel D. Lee

There have been many recent advances in representation learning; however, unsupervised representation learning can still struggle with model identification issues related to rotations of the latent space.

Disentanglement