b'Gautam Shroff'

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

∙ 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

∙ 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

∙ 10/19/2021

Forecasting Market Prices using DL with Data Augmentation and Meta-learning: ARIMA still wins!

Deep-learning techniques have been successfully used for time-series for...

Vedant Shah, 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

∙ 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

∙ 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

∙ 04/28/2020

Privacy Guidelines for Contact Tracing Applications

Contact tracing is a very powerful method to implement and enforce socia...

Manish Shukla, 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

∙ 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

∙ 05/31/2019

Fast Online "Next Best Offers" using Deep Learning

In this paper, we present iPrescribe, a scalable low-latency architectur...

Rekha Singhal, 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

∙ 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

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

∙ 07/04/2018

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

∙ 10/25/2017

Crop Planning using Stochastic Visual Optimization

As the world population increases and arable land decreases, it becomes ...

Gunjan Sehgal, et al. ∙

research

∙ 08/18/2017

Comparative Benchmarking of Causal Discovery Techniques

In this paper we present a comprehensive view of prominent causal discov...

Karamjit Singh, 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. ∙

research

∙ 11/11/2014

Warranty Cost Estimation Using Bayesian Network

All multi-component product manufacturing companies face the problem of ...

Karamjit Singh, et al. ∙

Gautam Shroff

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