b'Lovekesh Vig'

research

∙ 12/20/2022

Do I have the Knowledge to Answer? Investigating Answerability of Knowledge Base Questions

When answering natural language questions over knowledge bases (KBs), in...

Mayur Patidar, et al. ∙

research

∙ 12/20/2022

Real-time Health Monitoring of Heat Exchangers using Hypernetworks and PINNs

We demonstrate a Physics-informed Neural Network (PINN) based model for ...

Ritam Majumdar, et al. ∙

research

∙ 12/20/2022

Calibrating Deep Neural Networks using Explicit Regularisation and Dynamic Data Pruning

Deep neural networks (DNN) are prone to miscalibrated predictions, often...

Ramya Hebbalaguppe, et al. ∙

research

∙ 11/29/2022

Neural Feature-Adaptation for Symbolic Predictions Using Pre-Training and Semantic Loss

We are interested in neurosymbolic systems consisting of a high-level sy...

Vedant Shah, et al. ∙

research

∙ 09/19/2022

Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces

Analogical Reasoning problems challenge both connectionist and symbolic ...

Vishwa Shah, et al. ∙

research

∙ 07/11/2022

On NeuroSymbolic Solutions for PDEs

Physics Informed Neural Networks (PINNs) have gained immense popularity ...

Ritam Majumdar, et al. ∙

research

∙ 03/30/2022

An Efficient Anchor-free Universal Lesion Detection in CT-scans

Existing universal lesion detection (ULD) methods utilize compute-intens...

Manu Sheoran, et al. ∙

research

∙ 03/14/2022

DKMA-ULD: Domain Knowledge augmented Multi-head Attention based Robust Universal Lesion Detection

Incorporating data-specific domain knowledge in deep networks explicitly...

Manu Sheoran, et al. ∙

research

∙ 03/14/2022

TSR-DSAW: Table Structure Recognition via Deep Spatial Association of Words

Existing methods for Table Structure Recognition (TSR) from camera-captu...

Arushi Jain, et al. ∙

research

∙ 03/14/2022

Continual Learning for Multivariate Time Series Tasks with Variable Input Dimensions

We consider a sequence of related multivariate time series learning task...

Vibhor Gupta, et al. ∙

research

∙ 02/25/2022

Learning to Liquidate Forex: Optimal Stopping via Adaptive Top-K Regression

We consider learning a trading agent acting on behalf of the treasury of...

Diksha Garg, et al. ∙

research

∙ 02/11/2022

Electricity Consumption Forecasting for Out-of-distribution Time-of-Use Tariffs

In electricity markets, retailers or brokers want to maximize profits by...

Jyoti Narwariya, et al. ∙

research

∙ 01/20/2022

DRTCI: Learning Disentangled Representations for Temporal Causal Inference

Medical professionals evaluating alternative treatment plans for a patie...

Garima Gupta, et al. ∙

research

∙ 11/19/2021

Solving Visual Analogies Using Neural Algorithmic Reasoning

We consider a class of visual analogical reasoning problems that involve...

Atharv Sonwane, et al. ∙

research

∙ 10/31/2021

PnPOOD : Out-Of-Distribution Detection for Text Classification via Plug andPlay Data Augmentation

While Out-of-distribution (OOD) detection has been well explored in comp...

Mrinal Rawat, et al. ∙

research

∙ 10/19/2021

Using Program Synthesis and Inductive Logic Programming to solve Bongard Problems

The ability to recognise and make analogies is often used as a measure o...

Atharv Sonwane, et al. ∙

research

∙ 09/08/2021

OSSR-PID: One-Shot Symbol Recognition in P ID Sheets using Path Sampling and GCN

Piping and Instrumentation Diagrams (P ID) are ubiquitous in several m...

Shubham Paliwal, et al. ∙

research

∙ 09/08/2021

Digitize-PID: Automatic Digitization of Piping and Instrumentation Diagrams

Digitization of scanned Piping and Instrumentation diagrams(P ID), wid...

Shubham Paliwal, et al. ∙

research

∙ 12/19/2020

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...

Rishab Khincha, et al. ∙

research

∙ 12/16/2020

Batch-Constrained Distributional Reinforcement Learning for Session-based Recommendation

Most of the existing deep reinforcement learning (RL) approaches for ses...

Diksha Garg, et al. ∙

research

∙ 10/23/2020

Incorporating Symbolic Domain Knowledge into Graph Neural Networks

Our interest is in scientific problems with the following characteristic...

Tirtharaj Dash, et al. ∙

research

∙ 08/22/2020

Hi-CI: Deep Causal Inference in High Dimensions

We address the problem of counterfactual regression using causal inferen...

Ankit Sharma, et al. ∙

research

∙ 07/01/2020

Handling Variable-Dimensional Time Series with Graph Neural Networks

Several applications of Internet of Things(IoT) technology involve captu...

Vibhor Gupta, et al. ∙

research

∙ 06/30/2020

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

Automated equipment health monitoring from streaming multisensor time-se...

Jyoti Narwariya, et al. ∙

research

∙ 04/28/2020

MultiMBNN: Matched and Balanced Causal Inference with Neural Networks

Causal inference (CI) in observational studies has received a lot of att...

Ankit Sharma, et al. ∙

research

∙ 01/06/2020

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 ...

Shubham Paliwal, et al. ∙

research

∙ 12/09/2019

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

Performing inference on data obtained through observational studies is b...

Ankit Sharma, et al. ∙

research

∙ 11/21/2019

ChartNet: Visual Reasoning over Statistical Charts using MAC-Networks

Despite the improvements in perception accuracies brought about via deep...

Monika Sharma, et al. ∙

research

∙ 11/14/2019

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

Precise homography estimation between multiple images is a pre-requisite...

Kushagra Mahajan, et al. ∙

research

∙ 09/13/2019

Meta-Learning for Few-Shot Time Series Classification

Deep neural networks (DNNs) have achieved state-of-the-art results on ti...

Jyoti Narwariya, et al. ∙

research

∙ 09/10/2019

NISER: Normalized Item and Session Representations with Graph Neural Networks

The goal of session-based recommendation (SR) models is to utilize the i...

Priyanka Gupta, et al. ∙

research

∙ 07/16/2019

Meta-Learning for Black-box Optimization

Recently, neural networks trained as optimizers under the "learning to l...

Vishnu TV, et al. ∙

research

∙ 06/06/2019

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...

Vishal Sunder, et al. ∙

research

∙ 04/29/2019

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

Training deep neural networks often requires careful hyper-parameter tun...

Kathan Kashiparekh, et al. ∙

research

∙ 04/01/2019

Transfer Learning for Clinical Time Series Analysis using Deep Neural Networks

Deep neural networks have shown promising results for various clinical p...

Priyanka Gupta, et al. ∙

research

∙ 03/23/2019

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

Prognostics or Remaining Useful Life (RUL) Estimation from multi-sensor ...

Vishnu TV, et al. ∙

research

∙ 01/28/2019

Learning to Clean: A GAN Perspective

In the big data era, the impetus to digitize the vast reservoirs of data...

Monika Sharma, et al. ∙

research

∙ 01/28/2019

Automatic Information Extraction from Piping and Instrumentation Diagrams

One of the most common modes of representing engineering schematics are ...

Rohit Rahul, et al. ∙

research

∙ 12/28/2018

MEETING BOT: Reinforcement Learning for Dialogue Based Meeting Scheduling

In this paper we present Meeting Bot, a reinforcement learning based con...

Vishwanath D, et al. ∙

research

∙ 12/11/2018

Reading Industrial Inspection Sheets by Inferring Visual Relations

The traditional mode of recording faults in heavy factory equipment has ...

Rohit Rahul, et al. ∙

research

∙ 12/11/2018

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...

Vishwanath D, et al. ∙

research

∙ 09/19/2018

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

We present an effective technique for training deep learning agents capa...

Vishal Sunder, et al. ∙

research

∙ 07/20/2018

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

Offline handwritten text recognition from images is an important problem...

Arindam Chowdhury, et al. ∙

research

∙ 07/04/2018

Transfer Learning for Clinical Time Series Analysis using Recurrent Neural Networks

Deep neural networks have shown promising results for various clinical p...

Priyanka Gupta, et al. ∙

research

∙ 07/02/2018

Logical Explanations for Deep Relational Machines Using Relevance Information

Our interest in this paper is in the construction of symbolic explanatio...

Ashwin Srinivasan, et al. ∙

research

∙ 12/20/2016

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

We investigate solving discrete optimisation problems using the estimati...

Sarmimala Saikia, et al. ∙

research

∙ 08/03/2016

Generation of Near-Optimal Solutions Using ILP-Guided Sampling

Our interest in this paper is in optimisation problems that are intracta...

Ashwin Srinivasan, et al. ∙

research

∙ 07/01/2016

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

Mechanical devices such as engines, vehicles, aircrafts, etc., are typic...

Pankaj Malhotra, et al. ∙

Lovekesh Vig

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