10 citations · 18 across the 5 of their papers we have counts for
5 papers
Joint Learning of Hierarchical Neural Options and Abstract World Model
Wasu Top Piriyakulkij, Wolfgang Lehrach, Kevin Ellis +1
Building agents that can perform new skills by composing existing skills is a long-standing goal of AI agent research. Towards this end, we investigate how to efficiently acquire a…
Reinforcement Learning: An Overview
Kevin Murphy
This manuscript gives a big-picture, up-to-date overview of the field of (deep) reinforcement learning and sequential decision making, covering value-based methods, policy-based me…
EM Distillation for One-step Diffusion Models
Sirui Xie, Zhisheng Xiao, Diederik P Kingma +6
While diffusion models can learn complex distributions, sampling requires a computationally expensive iterative process. Existing distillation methods enable efficient sampling, bu…
BlackJAX: Composable Bayesian inference in JAX
Alberto Cabezas, Adrien Corenflos, Junpeng Lao +19
BlackJAX is a library implementing sampling and variational inference algorithms commonly used in Bayesian computation. It is designed for ease of use, speed, and modularity by tak…
Informative Priors Improve the Reliability of Multimodal Clinical Data Classification
L. Julian Lechuga Lopez, Tim G. J. Rudner, Farah E. Shamout
Machine learning-aided clinical decision support has the potential to significantly improve patient care. However, existing efforts in this domain for principled quantification of…