b'Lovekesh Vig'

Constructing and Evaluating an Explainable Model for COVID-19 Diagnosis from Chest X-rays

In this paper, our focus is on constructing models to assist a clinician...
12/19/2020 ∙ by Rishab Khincha, et al. ∙ 0 ∙ share

read it
Batch-Constrained Distributional Reinforcement Learning for Session-based Recommendation

Most of the existing deep reinforcement learning (RL) approaches for ses...
12/16/2020 ∙ by Diksha Garg, et al. ∙ 0 ∙ share

read it
Incorporating Symbolic Domain Knowledge into Graph Neural Networks

Our interest is in scientific problems with the following characteristic...
10/23/2020 ∙ by Tirtharaj Dash, et al. ∙ 0 ∙ share

read it
Hi-CI: Deep Causal Inference in High Dimensions

We address the problem of counterfactual regression using causal inferen...
08/22/2020 ∙ by Ankit Sharma, et al. ∙ 8 ∙ share

read it
Handling Variable-Dimensional Time Series with Graph Neural Networks

Several applications of Internet of Things(IoT) technology involve captu...
07/01/2020 ∙ by Vibhor Gupta, et al. ∙ 6 ∙ share

read it
Graph Neural Networks for Leveraging Industrial Equipment Structure: An application to Remaining Useful Life Estimation

Automated equipment health monitoring from streaming multisensor time-se...
06/30/2020 ∙ by Jyoti Narwariya, et al. ∙ 0 ∙ share

read it
MultiMBNN: Matched and Balanced Causal Inference with Neural Networks

Causal inference (CI) in observational studies has received a lot of att...
04/28/2020 ∙ by Ankit Sharma, et al. ∙ 0 ∙ share

read it
TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images

With the widespread use of mobile phones and scanners to photograph and ...
01/06/2020 ∙ by Shubham Paliwal, et al. ∙ 34 ∙ share

read it
MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population

Performing inference on data obtained through observational studies is b...
12/09/2019 ∙ by Ankit Sharma, et al. ∙ 0 ∙ share

read it
ChartNet: Visual Reasoning over Statistical Charts using MAC-Networks

Despite the improvements in perception accuracies brought about via deep...
11/21/2019 ∙ by Monika Sharma, et al. ∙ 0 ∙ share

read it
Character Keypoint-based Homography Estimation in Scanned Documents for Efficient Information Extraction

Precise homography estimation between multiple images is a pre-requisite...
11/14/2019 ∙ by Kushagra Mahajan, et al. ∙ 8 ∙ share

read it
Meta-Learning for Few-Shot Time Series Classification

Deep neural networks (DNNs) have achieved state-of-the-art results on ti...
09/13/2019 ∙ by Jyoti Narwariya, et al. ∙ 0 ∙ share

read it
NISER: Normalized Item and Session Representations with Graph Neural Networks

The goal of session-based recommendation (SR) models is to utilize the i...
09/10/2019 ∙ by Priyanka Gupta, et al. ∙ 0 ∙ share

read it
Meta-Learning for Black-box Optimization

Recently, neural networks trained as optimizers under the "learning to l...
07/16/2019 ∙ by Vishnu TV, et al. ∙ 0 ∙ share

read it
One-shot Information Extraction from Document Images using Neuro-Deductive Program Synthesis

Our interest in this paper is in meeting a rapidly growing industrial de...
06/06/2019 ∙ by Vishal Sunder, et al. ∙ 0 ∙ share

read it
ConvTimeNet: A Pre-trained Deep Convolutional Neural Network for Time Series Classification

Training deep neural networks often requires careful hyper-parameter tun...
04/29/2019 ∙ by Kathan Kashiparekh, et al. ∙ 0 ∙ share

read it
Transfer Learning for Clinical Time Series Analysis using Deep Neural Networks

Deep neural networks have shown promising results for various clinical p...
04/01/2019 ∙ by Priyanka Gupta, et al. ∙ 0 ∙ share

read it
Data-driven Prognostics with Predictive Uncertainty Estimation using Ensemble of Deep Ordinal Regression Models

Prognostics or Remaining Useful Life (RUL) Estimation from multi-sensor ...
03/23/2019 ∙ by Vishnu TV, et al. ∙ 0 ∙ share

read it
Learning to Clean: A GAN Perspective

In the big data era, the impetus to digitize the vast reservoirs of data...
01/28/2019 ∙ by Monika Sharma, et al. ∙ 0 ∙ share

read it
Automatic Information Extraction from Piping and Instrumentation Diagrams

One of the most common modes of representing engineering schematics are ...
01/28/2019 ∙ by Rohit Rahul, et al. ∙ 0 ∙ share

read it
MEETING BOT: Reinforcement Learning for Dialogue Based Meeting Scheduling

In this paper we present Meeting Bot, a reinforcement learning based con...
12/28/2018 ∙ by Vishwanath D, et al. ∙ 0 ∙ share

read it
Reading Industrial Inspection Sheets by Inferring Visual Relations

The traditional mode of recording faults in heavy factory equipment has ...
12/11/2018 ∙ by Rohit Rahul, et al. ∙ 0 ∙ share

read it
Deep Reader: Information extraction from Document images via relation extraction and Natural Language

Recent advancements in the area of Computer Vision with state-of-art Neu...
12/11/2018 ∙ by Vishwanath D, et al. ∙ 0 ∙ share

read it
Prosocial or Selfish? Agents with different behaviors for Contract Negotiation using Reinforcement Learning

We present an effective technique for training deep learning agents capa...
09/19/2018 ∙ by Vishal Sunder, et al. ∙ 0 ∙ share

read it
An Efficient End-to-End Neural Model for Handwritten Text Recognition

Offline handwritten text recognition from images is an important problem...
07/20/2018 ∙ by Arindam Chowdhury, et al. ∙ 0 ∙ share

read it
Transfer Learning for Clinical Time Series Analysis using Recurrent Neural Networks

Deep neural networks have shown promising results for various clinical p...
07/04/2018 ∙ by Priyanka Gupta, et al. ∙ 0 ∙ share

read it
Logical Explanations for Deep Relational Machines Using Relevance Information

Our interest in this paper is in the construction of symbolic explanatio...
07/02/2018 ∙ by Ashwin Srinivasan, et al. ∙ 0 ∙ share

read it
Neuro-symbolic EDA-based Optimisation using ILP-enhanced DBNs

We investigate solving discrete optimisation problems using the estimati...
12/20/2016 ∙ by Sarmimala Saikia, et al. ∙ 0 ∙ share

read it
Generation of Near-Optimal Solutions Using ILP-Guided Sampling

Our interest in this paper is in optimisation problems that are intracta...
08/03/2016 ∙ by Ashwin Srinivasan, et al. ∙ 0 ∙ share

read it
LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Mechanical devices such as engines, vehicles, aircrafts, etc., are typic...
07/01/2016 ∙ by Pankaj Malhotra, et al. ∙ 0 ∙ share

read it

Lovekesh Vig

Featured Co-authors