5 citations · 10 across the 8 of their papers we have counts for
5 papers · 1 filter
Automated Adversary Emulation for Cyber-Physical Systems via Reinforcement Learning
Arnab Bhattacharya, Thiagarajan Ramachandran, Sandeep Banik +2
Adversary emulation is an offensive exercise that provides a comprehensive assessment of a system's resilience against cyber attacks. However, adversary emulation is typically a ma…
GraphReach: Position-Aware Graph Neural Network using Reachability Estimations
Sunil Nishad, Shubhangi Agarwal, Arnab Bhattacharya +1
Majority of the existing graph neural networks (GNN) learn node embeddings that encode their local neighborhoods but not their positions. Consequently, two nodes that are vastly di…
How and Why is An Answer (Still) Correct? Maintaining Provenance in Dynamic Knowledge Graphs
Garima Gaur, Arnab Bhattacharya, Srikanta Bedathur
Knowledge graphs (KGs) have increasingly become the backbone of many critical knowledge-centric applications. Most large-scale KGs used in practice are automatically constructed ba…
Learning Koopman Representations for Hybrid Systems
Craig Bakker, Arnab Bhattacharya, Samrat Chatterjee +2
The Koopman operator lifts nonlinear dynamical systems into a functional space of observables, where the dynamics are linear. In this paper, we provide three different Koopman repr…
Model Predictive Control of Discrete-Continuous Energy Systems via Generalized Disjunctive Programming
Arnab Bhattacharya, Xu Ma, Draguna Vrabie
Generalized Disjunctive Programming (GDP) provides an alternative framework to model optimization problems with both discrete and continuous variables. The key idea behind GDP invo…