research
∙
08/18/2023
How important are specialized transforms in Neural Operators?
Simulating physical systems using Partial Differential Equations (PDEs) ...
share
research
∙
08/18/2023
HyperLoRA for PDEs
Physics-informed neural networks (PINNs) have been widely used to develo...
research
∙
08/01/2023
Adapt and Decompose: Efficient Generalization of Text-to-SQL via Domain Adapted Least-To-Most Prompting
Cross-domain and cross-compositional generalization of Text-to-SQL seman...
research
∙
04/26/2023
Neuro-symbolic Zero-Shot Code Cloning with Cross-Language Intermediate Representation
In this paper, we define a neuro-symbolic approach to address the task o...
research
∙
03/24/2023
DeepEpiSolver: Unravelling Inverse problems in Covid, HIV, Ebola and Disease Transmission
The spread of many infectious diseases is modeled using variants of the ...
research
∙
03/16/2023
Knowledge Transfer for Pseudo-code Generation from Low Resource Programming Language
Generation of pseudo-code descriptions of legacy source code for softwar...
research
∙
03/13/2023
Symbolic Regression for PDEs using Pruned Differentiable Programs
Physics-informed Neural Networks (PINNs) have been widely used to obtain...
research
∙
03/04/2023
IKD+: Reliable Low Complexity Deep Models For Retinopathy Classification
Deep neural network (DNN) models for retinopathy have estimated predicti...
research
∙
02/20/2023
Domain-Specific Pretraining Improves Confidence in Whole Slide Image Classification
Whole Slide Images (WSIs) or histopathology images are used in digital p...
research
∙
01/15/2023
Neuro-symbolic Meta Reinforcement Learning for Trading
We model short-duration (e.g. day) trading in financial markets as a seq...
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...
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 ...
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...
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...
research
∙
09/19/2022
Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces
Analogical Reasoning problems challenge both connectionist and symbolic ...
research
∙
07/11/2022
On NeuroSymbolic Solutions for PDEs
Physics Informed Neural Networks (PINNs) have gained immense popularity ...
research
∙
03/30/2022
An Efficient Anchor-free Universal Lesion Detection in CT-scans
Existing universal lesion detection (ULD) methods utilize compute-intens...
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...
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...
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...
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...
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...
research
∙
01/20/2022
DRTCI: Learning Disentangled Representations for Temporal Causal Inference
Medical professionals evaluating alternative treatment plans for a patie...
research
∙
11/19/2021
Solving Visual Analogies Using Neural Algorithmic Reasoning
We consider a class of visual analogical reasoning problems that involve...
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...
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...
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...
research
∙
09/08/2021
Digitize-PID: Automatic Digitization of Piping and Instrumentation Diagrams
Digitization of scanned Piping and Instrumentation diagrams(P ID), wid...
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...
research
∙
12/16/2020
Batch-Constrained Distributional Reinforcement Learning for Session-based Recommendation
Most of the existing deep reinforcement learning (RL) approaches for ses...
research
∙
10/23/2020
Incorporating Symbolic Domain Knowledge into Graph Neural Networks
Our interest is in scientific problems with the following characteristic...
research
∙
08/22/2020
Hi-CI: Deep Causal Inference in High Dimensions
We address the problem of counterfactual regression using causal inferen...
research
∙
07/01/2020
Handling Variable-Dimensional Time Series with Graph Neural Networks
Several applications of Internet of Things(IoT) technology involve captu...
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...
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...
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 ...
research
∙
12/09/2019
MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population
Performing inference on data obtained through observational studies is b...
research
∙
11/21/2019
ChartNet: Visual Reasoning over Statistical Charts using MAC-Networks
Despite the improvements in perception accuracies brought about via deep...
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...
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...
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...
research
∙
07/16/2019
Meta-Learning for Black-box Optimization
Recently, neural networks trained as optimizers under the "learning to l...
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...
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...
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...
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 ...
research
∙
01/28/2019
Learning to Clean: A GAN Perspective
In the big data era, the impetus to digitize the vast reservoirs of data...
research
∙
01/28/2019
Automatic Information Extraction from Piping and Instrumentation Diagrams
One of the most common modes of representing engineering schematics are ...
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...
research
∙
12/11/2018
