Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series
We develop a family of stable continuous-time neural state space-models.
Posts
Laruso blog features productivity, tips, inspiration and strategies for massive profits. Find out how to set up a successful blog or how to make yours even better!
Introducing Dr. Xie Yaqi.
Xie Yaqi successfully defended her thesis and is now Dr. Xie. Congratulations Yaqi! You can find out more about Yaqi’s work on embedding symbolic knowledg...
Translating Natural Language to Planning Goals with Large-Language Models
We contribute an empirical study into the effectiveness of LLMs, specifically GPT-3.5 variants, for the task of natural language goal translation to PDDL.
Safety-Constrained Policy Transfer with Successor Features
Transfer source policies to a target reinforcement learning task with safety constraints using Successor Features.
Observed Adversaries in Deep Reinforcement Learning
We examine the problem of observed adversaries for deep policies, where observations of other agents can hamper robot performance.
IEEE T-AFFC Best Paper Award!
Our joint work with Desmond Ong, Jamil Zaki and Noah Goodman on Applying Probabilistic Programming to Affective Computing is one of 5 Best Papers (out of 82 ...
Fairness meets CMDPs
This paper proposes SCALES, a general framework that translates well-established fairness principles into a common representation based on CMDPs.
