51 citations · 53 across the 3 of their papers we have counts for
3 papers
CrystalBox: Future-Based Explanations for Input-Driven Deep RL Systems
Sagar Patel, Sangeetha Abdu Jyothi, Nina Narodytska
We present CrystalBox, a novel, model-agnostic, posthoc explainability framework for Deep Reinforcement Learning (DRL) controllers in the large family of input-driven environments…
Plume: A Framework for High Performance Deep RL Network Controllers via Prioritized Trace Sampling
Sagar Patel, Junyang Zhang, Sangeetha Abdu Jyothi +1
Deep Reinforcement Learning (DRL) has shown promise in various networking environments. However, these environments present several fundamental challenges for standard DRL techniqu…
3D Topology Optimization using Convolutional Neural Networks
Saurabh Banga, Harsh Gehani, Sanket Bhilare +2
Topology optimization is computationally demanding that requires the assembly and solution to a finite element problem for each material distribution hypothesis. As a complementary…