13 citations · 13 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 13 cited
MABe22: A Multi-Species Multi-Task Benchmark for Learned Representations of Behavior
Jennifer J. Sun, Markus Marks, Andrew Ulmer +20
We introduce MABe22, a large-scale, multi-agent video and trajectory benchmark to assess the quality of learned behavior representations. This dataset is collected from a variety o…
cs.LG2020
Robust Disentanglement of a Few Factors at a Time
Benjamin Estermann, Markus Marks, Mehmet Fatih Yanik
Disentanglement is at the forefront of unsupervised learning, as disentangled representations of data improve generalization, interpretability, and performance in downstream tasks.…