activity
20192025
most citedRecurrent Control Nets for Deep Reinforcement Learning

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2025

Probabilistic Circuits for Knowledge Graph Completion with Reduced Rule Sets

Jaikrishna Manojkumar Patil, Nathaniel Lee, Al Mehdi Saadat Chowdhury +2

Rule-based methods for knowledge graph completion provide explainable results, but often require tens of thousands of rules to achieve competitive performance. Although individual…

cs.AI2025

Sea-cret Agents: Maritime Abduction for Region Generation to Expose Dark Vessel Trajectories

Divyagna Bavikadi, Nathaniel Lee, Paulo Shakarian +1

Bad actors in the maritime industry engage in illegal behaviors after disabling their vessel's automatic identification system (AIS) - which makes finding such vessels difficult fo…

cs.LG2024

Metal Price Spike Prediction via a Neurosymbolic Ensemble Approach

Nathaniel Lee, Noel Ngu, Harshdeep Singh Sahdev +4

Predicting price spikes in critical metals such as Cobalt, Copper, Magnesium, and Nickel is crucial for mitigating economic risks associated with global trends like the energy tran…

cs.CL2023★ 1 cited

Diversity Measures: Domain-Independent Proxies for Failure in Language Model Queries

Noel Ngu, Nathaniel Lee, Paulo Shakarian

Error prediction in large language models often relies on domain-specific information. In this paper, we present measures for quantification of error in the response of a large lan…

cs.LG2019★ 1 cited

Recurrent Control Nets for Deep Reinforcement Learning

Vincent Liu, Ademi Adeniji, Nathaniel Lee +2

Central Pattern Generators (CPGs) are biological neural circuits capable of producing coordinated rhythmic outputs in the absence of rhythmic input. As a result, they are responsib…