1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Maximum Likelihood Learning of Latent Dynamics Without Reconstruction
Samo Hromadka, Kai Biegun, Lior Fox +2
We introduce a novel unsupervised learning method for time series data with latent dynamical structure: the recognition-parametrized Gaussian state space model (RP-GSSM). The RP-GS…
cs.LG2024
Fast unsupervised ground metric learning with tree-Wasserstein distance
Kira M. Düsterwald, Samo Hromadka, Makoto Yamada
The performance of unsupervised methods such as clustering depends on the choice of distance metric between features, or ground metric. Commonly, ground metrics are decided with he…
cs.LG2023★ 1 cited
A State Representation for Diminishing Rewards
Ted Moskovitz, Samo Hromadka, Ahmed Touati +2
A common setting in multitask reinforcement learning (RL) demands that an agent rapidly adapt to various stationary reward functions randomly sampled from a fixed distribution. In…