35 citations · 51 across the 12 of their papers we have counts for
14 papers
Multi-Modal Financial Time-Series Retrieval Through Latent Space Projections
Tom Bamford, Andrea Coletta, Elizabeth Fons +4
Financial firms commonly process and store billions of time-series data, generated continuously and at a high frequency. To support efficient data storage and retrieval, specialize…
SafeAR: Safe Algorithmic Recourse by Risk-Aware Policies
Haochen Wu, Shubham Sharma, Sunandita Patra +1
With the growing use of machine learning (ML) models in critical domains such as finance and healthcare, the need to offer recourse for those adversely affected by the decisions of…
On the Constrained Time-Series Generation Problem
Andrea Coletta, Sriram Gopalakrishan, Daniel Borrajo +1
Synthetic time series are often used in practical applications to augment the historical time series dataset for better performance of machine learning algorithms, amplify the occu…
Methods and Mechanisms for Interactive Novelty Handling in Adversarial Environments
Tung Thai, Ming Shen, Mayank Garg +10
Learning to detect, characterize and accommodate novelties is a challenge that agents operating in open-world domains need to address to be able to guarantee satisfactory task perf…
pyRDDLGym: From RDDL to Gym Environments
Ayal Taitler, Michael Gimelfarb, Jihwan Jeong +4
We present pyRDDLGym, a Python framework for auto-generation of OpenAI Gym environments from RDDL declerative description. The discrete time step evolution of variables in RDDL is…
Computing Policies That Account For The Effects Of Human Agent Uncertainty During Execution In Markov Decision Processes
Sriram Gopalakrishnan, Mudit Verma, Subbarao Kambhampati
When humans are given a policy to execute, there can be policy execution errors and deviations in policy if there is uncertainty in identifying a state. This can happen due to the…
Integrating Planning, Execution and Monitoring in the presence of Open World Novelties: Case Study of an Open World Monopoly Solver
Sriram Gopalakrishnan, Utkarsh Soni, Tung Thai +3
The game of monopoly is an adversarial multi-agent domain where there is no fixed goal other than to be the last player solvent, There are useful subgoals like monopolizing sets of…
Long-range connectivity in a superconducting quantum processor using a ring resonator
Sumeru Hazra, Anirban Bhattacharjee, Madhavi Chand +4
Qubit coherence and gate fidelity are typically considered the two most important metrics for characterizing a quantum processor. An equally important metric is inter-qubit connect…
Goal recognition via model-based and model-free techniques
Daniel Borrajo, Sriram Gopalakrishnan, Vamsi K. Potluru
Goal recognition aims at predicting human intentions from a trace of observations. This ability allows people or organizations to anticipate future actions and intervene in a posit…
Minimizing Robot Navigation-Graph For Position-Based Predictability By Humans
Sriram Gopalakrishnan, Subbarao Kambhampati
In situations where humans and robots are moving in the same space whilst performing their own tasks, predictable paths taken by mobile robots can not only make the environment fee…
Landau quantization of a circular Quantum Dot using the BenDaniel-Duke boundary condition
Sriram Gopalakrishnan, Sayak Biswas, Shivam Handa
We derive the energy levels of a circular Quantum Dot (QD) under a transverse magnetic field, incorporating the Ben-Daniel Duke boundary condition (BDD). The parameters in our mode…
Embedding Directed Graphs in Potential Fields Using FastMap-D
Sriram Gopalakrishnan, Liron Cohen, Sven Koenig +1
Embedding undirected graphs in a Euclidean space has many computational benefits. FastMap is an efficient embedding algorithm that facilitates a geometric interpretation of problem…
TGE-viz : Transition Graph Embedding for Visualization of Plan Traces and Domains
Sriram Gopalakrishnan, Subbarao Kambhampati
Existing work for plan trace visualization in automated planning uses pipeline-style visualizations, similar to plans in Gantt charts. Such visualization do not capture the domain…
Recognizing Plans by Learning Embeddings from Observed Action Distributions
Yantian Zha, Yikang Li, Sriram Gopalakrishnan +2
Recent advances in visual activity recognition have raised the possibility of applications such as automated video surveillance. Effective approaches for such problems however requ…