2 citations · 4 across the 9 of their papers we have counts for
9 papers
Contextual Tokenization for Graph Inverted Indices
Pritish Chakraborty, Indradyumna Roy, Soumen Chakrabarti +1
Retrieving graphs from a large corpus, that contain a subgraph isomorphic to a given query graph, is a core operation in many real-world applications. While recent multi-vector gra…
Charting the Design Space of Neural Graph Representations for Subgraph Matching
Vaibhav Raj, Indradyumna Roy, Ashwin Ramachandran +2
Subgraph matching is vital in knowledge graph (KG) question answering, molecule design, scene graph, code and circuit search, etc. Neural methods have shown promising results for s…
Iteratively Refined Early Interaction Alignment for Subgraph Matching based Graph Retrieval
Ashwin Ramachandran, Vaibhav Raj, Indrayumna Roy +2
Graph retrieval based on subgraph isomorphism has several real-world applications such as scene graph retrieval, molecular fingerprint detection and circuit design. Roy et al. [35]…
Monotone and Separable Set Functions: Characterizations and Neural Models
Soutrik Sarangi, Yonatan Sverdlov, Nadav Dym +1
Motivated by applications for set containment problems, we consider the following fundamental problem: can we design set-to-vector functions so that the natural partial order on se…
Differentiable Adversarial Attacks for Marked Temporal Point Processes
Pritish Chakraborty, Vinayak Gupta, Rahul R +2
Marked temporal point processes (MTPPs) have been shown to be extremely effective in modeling continuous time event sequences (CTESs). In this work, we present adversarial attacks…
Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks
Eeshaan Jain, Tushar Nandy, Gaurav Aggarwal +3
Existing subset selection methods for efficient learning predominantly employ discrete combinatorial and model-specific approaches which lack generalizability. For an unseen archit…
Graph Edit Distance with General Costs Using Neural Set Divergence
Eeshaan Jain, Indradyumna Roy, Saswat Meher +2
Graph Edit Distance (GED) measures the (dis-)similarity between two given graphs, in terms of the minimum-cost edit sequence that transforms one graph to the other. However, the ex…
Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing
Lokesh Nagalapatti, Akshay Iyer, Abir De +1
We address the Individualized continuous treatment effect (ICTE) estimation problem where we predict the effect of any continuous-valued treatment on an individual using observatio…
Generator Assisted Mixture of Experts For Feature Acquisition in Batch
Vedang Asgaonkar, Aditya Jain, Abir De
Given a set of observations, feature acquisition is about finding the subset of unobserved features which would enhance accuracy. Such problems have been explored in a sequential s…