22 citations · 58 across the 12 of their papers we have counts for
13 papers
Thinking Fast and Laterally: Multi-Agentic Approach for Reasoning about Uncertain Emerging Events
Stefan Dernbach, Alejandro Michel, Khushbu Agarwal +3
This paper introduces lateral thinking to implement System-2 reasoning capabilities in AI systems, focusing on anticipatory and causal reasoning under uncertainty. We present a fra…
ChemReasoner: Heuristic Search over a Large Language Model's Knowledge Space using Quantum-Chemical Feedback
Henry W. Sprueill, Carl Edwards, Khushbu Agarwal +6
The discovery of new catalysts is essential for the design of new and more efficient chemical processes in order to transition to a sustainable future. We introduce an AI-guided co…
GLaM: Fine-Tuning Large Language Models for Domain Knowledge Graph Alignment via Neighborhood Partitioning and Generative Subgraph Encoding
Stefan Dernbach, Khushbu Agarwal, Alejandro Zuniga +2
Integrating large language models (LLMs) with knowledge graphs derived from domain-specific data represents an important advancement towards more powerful and factual reasoning. As…
A Unification Framework for Euclidean and Hyperbolic Graph Neural Networks
Mehrdad Khatir, Nurendra Choudhary, Sutanay Choudhury +2
Hyperbolic neural networks can effectively capture the inherent hierarchy of graph datasets, and consequently a powerful choice of GNNs. However, they entangle multiple incongruent…
Graph Neural Network and Koopman Models for Learning Networked Dynamics: A Comparative Study on Power Grid Transients Prediction
Sai Pushpak Nandanoori, Sheng Guan, Soumya Kundu +4
Continuous monitoring of the spatio-temporal dynamic behavior of critical infrastructure networks, such as the power systems, is a challenging but important task. In particular, ac…
Attention-based Aspect Reasoning for Knowledge Base Question Answering on Clinical Notes
Ping Wang, Tian Shi, Khushbu Agarwal +2
Question Answering (QA) in clinical notes has gained a lot of attention in the past few years. Existing machine reading comprehension approaches in clinical domain can only handle…
Model-Agnostic Algorithm for Real-Time Attack Identification in Power Grid using Koopman Modes
Sai Pushpak Nandanoori, Soumya Kundu, Seemita Pal +2
Malicious activities on measurements from sensors like Phasor Measurement Units (PMUs) can mislead the control center operator into taking wrong control actions resulting in disrup…
Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks
Ping Wang, Khushbu Agarwal, Colby Ham +2
Representation learning methods for heterogeneous networks produce a low-dimensional vector embedding for each node that is typically fixed for all tasks involving the node. Many o…
Snomed2Vec: Random Walk and Poincaré Embeddings of a Clinical Knowledge Base for Healthcare Analytics
Khushbu Agarwal, Tome Eftimov, Raghavendra Addanki +3
Representation learning methods that transform encoded data (e.g., diagnosis and drug codes) into continuous vector spaces (i.e., vector embeddings) are critical for the applicatio…
NOUS: Construction and Querying of Dynamic Knowledge Graphs
Sutanay Choudhury, Khushbu Agarwal, Sumit Purohit +4
The ability to construct domain specific knowledge graphs (KG) and perform question-answering or hypothesis generation is a transformative capability. Despite their value, automate…
Trust from the past: Bayesian Personalized Ranking based Link Prediction in Knowledge Graphs
Baichuan Zhang, Sutanay Choudhury, Mohammad Al Hasan +4
Link prediction, or predicting the likelihood of a link in a knowledge graph based on its existing state is a key research task. It differs from a traditional link prediction task…
A Selectivity based approach to Continuous Pattern Detection in Streaming Graphs
Sutanay Choudhury, Lawrence Holder, George Chin +2
Cyber security is one of the most significant technical challenges in current times. Detecting adversarial activities, prevention of theft of intellectual properties and customer d…
Query Optimization for Dynamic Graphs
Sutanay Choudhury, Lawrence Holder, George Chin +3
Given a query graph that represents a pattern of interest, the emerging pattern detection problem can be viewed as a continuous query problem on a dynamic graph. We present an incr…