Chandan K. Reddy

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Yan Li
103 publications
Ping Wang
60 publications
Amir Barati Farimani
47 publications
Naren Ramakrishnan
41 publications
Parminder Bhatia
33 publications
Lluis Marquez
29 publications
Nikhil Rao
28 publications
Vinodkumar Prabhakaran
28 publications
Xuchao Zhang
27 publications
Sumeet Katariya
19 publications
Sunipa Dev
19 publications

research

∙ 05/30/2023

Graph-based Multi-ODE Neural Networks for Spatio-Temporal Traffic Forecasting

There is a recent surge in the development of spatio-temporal forecastin...

0 Zibo Liu, et al. ∙

research

∙ 05/19/2023

SeeGULL: A Stereotype Benchmark with Broad Geo-Cultural Coverage Leveraging Generative Models

Stereotype benchmark datasets are crucial to detect and mitigate social ...

0 Akshita Jha, et al. ∙

research

∙ 05/02/2023

Complex Logical Reasoning over Knowledge Graphs using Large Language Models

Reasoning over knowledge graphs (KGs) is a challenging task that require...

0 Nurendra Choudhary, et al. ∙

research

∙ 03/23/2023

Self-Supervised Clustering of Multivariate Time-Series Data for Identifying TBI Physiological States

Determining clinically relevant physiological states from multivariate t...

0 Hamid Ghaderi, et al. ∙

research

∙ 03/13/2023

Transformer-based Planning for Symbolic Regression

Symbolic regression (SR) is a challenging task in machine learning that ...

0 Parshin Shojaee, et al. ∙

research

∙ 02/27/2023

A Self-Supervised Learning-based Approach to Clustering Multivariate Time-Series Data with Missing Values (SLAC-Time): An Application to Traumatic Brain Injury Phenotyping

Self-supervised learning approaches provide a promising direction for cl...

0 Hamid Ghaderi, et al. ∙

research

∙ 02/07/2023

Transformer-based Models for Long-Form Document Matching: Challenges and Empirical Analysis

Recent advances in the area of long document matching have primarily foc...

19 Akshita Jha, et al. ∙

research

∙ 01/31/2023

Execution-based Code Generation using Deep Reinforcement Learning

The utilization of programming language (PL) models, pretrained on large...

0 Parshin Shojaee, et al. ∙

research

∙ 11/11/2022

WindowSHAP: An Efficient Framework for Explaining Time-series Classifiers based on Shapley Values

Unpacking and comprehending how deep learning algorithms make decisions ...

0 Amin Nayebi, et al. ∙

research

∙ 08/13/2022

An Empirical Comparison of Explainable Artificial Intelligence Methods for Clinical Data: A Case Study on Traumatic Brain Injury

A longstanding challenge surrounding deep learning algorithms is unpacki...

0 Amin Nayebi, et al. ∙

research

∙ 07/06/2022

Text Enriched Sparse Hyperbolic Graph Convolutional Networks

Heterogeneous networks, which connect informative nodes containing text ...

0 Nurendra Choudhary, et al. ∙

research

∙ 06/16/2022

XLCoST: A Benchmark Dataset for Cross-lingual Code Intelligence

Recent advances in machine learning have significantly improved the unde...

10 Ming Zhu, et al. ∙

research

∙ 06/14/2022

Shopping Queries Dataset: A Large-Scale ESCI Benchmark for Improving Product Search

Improving the quality of search results can significantly enhance users ...

0 Chandan K. Reddy, et al. ∙

research

∙ 06/10/2022

StructCoder: Structure-Aware Transformer for Code Generation

There has been a recent surge of interest in automating software enginee...

0 Sindhu Tipirneni, et al. ∙

research

∙ 06/09/2022

Pseudo-Poincaré: A Unification Framework for Euclidean and Hyperbolic Graph Neural Networks

Hyperbolic neural networks have recently gained significant attention du...

0 Mehrdad Khatir, et al. ∙

research

∙ 06/07/2022

Towards Scalable Hyperbolic Neural Networks using Taylor Series Approximations

Hyperbolic networks have shown prominent improvements over their Euclide...

0 Nurendra Choudhary, et al. ∙

research

∙ 05/31/2022

CodeAttack: Code-based Adversarial Attacks for Pre-Trained Programming Language Models

Pre-trained programming language (PL) models (such as CodeT5, CodeBERT, ...

2 Akshita Jha, et al. ∙

research

∙ 10/26/2021

Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs

Logical reasoning over Knowledge Graphs (KGs) is a fundamental technique...

0 Nurendra Choudhary, et al. ∙

research

∙ 08/20/2021

Supervised Contrastive Learning for Interpretable Long Document Comparison

Recent advancements in deep learning techniques have transformed the are...

0 Akshita Jha, et al. ∙

research

∙ 07/31/2021

Fair Representation Learning using Interpolation Enabled Disentanglement

With the growing interest in the machine learning community to solve rea...

8 Akshita Jha, et al. ∙

research

∙ 07/29/2021

Self-supervised Transformer for Multivariate Clinical Time-Series with Missing Values

Multivariate time-series (MVTS) data are frequently observed in critical...

0 Sindhu Tipirneni, et al. ∙

research

∙ 06/09/2021

Self-Supervised Graph Learning with Hyperbolic Embedding for Temporal Health Event Prediction

Electronic Health Records (EHR) have been heavily used in modern healthc...

0 Chang Lu, et al. ∙

research

∙ 05/16/2021

Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare

Accurate and explainable health event predictions are becoming crucial f...

0 Chang Lu, et al. ∙

research

∙ 04/05/2021

Jekyll: Attacking Medical Image Diagnostics using Deep Generative Models

Advances in deep neural networks (DNNs) have shown tremendous promise in...

31 Neal Mangaokar, et al. ∙

research

∙ 03/07/2021

T-Miner: A Generative Approach to Defend Against Trojan Attacks on DNN-based Text Classification

Deep Neural Network (DNN) classifiers are known to be vulnerable to Troj...

0 Ahmadreza Azizi, et al. ∙

research

∙ 12/23/2020

Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs

Knowledge Graphs (KGs) are ubiquitous structures for information storage...

0 Nurendra Choudhary, et al. ∙

research

∙ 12/22/2020

Differentially Private Synthetic Medical Data Generation using Convolutional GANs

Deep learning models have demonstrated superior performance in several a...

29 Amirsina Torfi, et al. ∙

research

∙ 07/22/2020

Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks

Representation learning methods for heterogeneous networks produce a low...

0 Ping Wang, et al. ∙

research

∙ 04/24/2020

A Concept-based Abstraction-Aggregation Deep Neural Network for Interpretable Document Classification

Using attention weights to identify information that is important for mo...

0 Tian Shi, et al. ∙

research

∙ 03/26/2020

Image Generation Via Minimizing Fréchet Distance in Discriminator Feature Space

For a given image generation problem, the intrinsic image manifold is of...

4 Khoa D. Doan, et al. ∙

research

∙ 02/29/2020

Image Hashing by Minimizing Independent Relaxed Wasserstein Distance

Image hashing is a fundamental problem in the computer vision domain wit...

0 Khoa D. Doan, et al. ∙

research

∙ 11/21/2019

LATTE: Latent Type Modeling for Biomedical Entity Linking

Entity linking is the task of linking mentions of named entities in natu...

0 Ming Zhu, et al. ∙

research

∙ 07/28/2019

A Translate-Edit Model for Natural Language Question to SQL Query Generation on Multi-relational Healthcare Data

Electronic health record (EHR) data contains most of the important patie...

0 Ping Wang, et al. ∙

research

∙ 05/28/2019

LeafNATS: An Open-Source Toolkit and Live Demo System for Neural Abstractive Text Summarization

Neural abstractive text summarization (NATS) has received a lot of atten...

0 Tian Shi, et al. ∙

research

∙ 12/05/2018

Neural Abstractive Text Summarization with Sequence-to-Sequence Models

In the past few years, neural abstractive text summarization with sequen...

8 Tian Shi, et al. ∙

research

∙ 10/15/2018

Deep Transfer Reinforcement Learning for Text Summarization

Deep neural networks are data hungry models and thus they face difficult...

6 Yaser Keneshloo, et al. ∙

research

∙ 05/24/2018

Deep Reinforcement Learning For Sequence to Sequence Models

In recent years, sequence-to-sequence (seq2seq) models are used in a var...

0 Yaser Keneshloo, et al. ∙

research

∙ 08/15/2017

Machine Learning for Survival Analysis: A Survey

Accurately predicting the time of occurrence of an event of interest is ...

0 Ping Wang, et al. ∙

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