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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...
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01/15/2023
Neuro-symbolic Meta Reinforcement Learning for Trading
We model short-duration (e.g. day) trading in financial markets as a seq...
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12/20/2022
Calibrating Deep Neural Networks using Explicit Regularisation and Dynamic Data Pruning
Deep neural networks (DNN) are prone to miscalibrated predictions, often...
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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...
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09/19/2022
Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces
Analogical Reasoning problems challenge both connectionist and symbolic ...
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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...
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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...
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01/20/2022
DRTCI: Learning Disentangled Representations for Temporal Causal Inference
Medical professionals evaluating alternative treatment plans for a patie...
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11/19/2021
Solving Visual Analogies Using Neural Algorithmic Reasoning
We consider a class of visual analogical reasoning problems that involve...
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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...
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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...
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12/16/2020
Batch-Constrained Distributional Reinforcement Learning for Session-based Recommendation
Most of the existing deep reinforcement learning (RL) approaches for ses...
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08/22/2020
Hi-CI: Deep Causal Inference in High Dimensions
We address the problem of counterfactual regression using causal inferen...
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07/01/2020
Handling Variable-Dimensional Time Series with Graph Neural Networks
Several applications of Internet of Things(IoT) technology involve captu...
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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...
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04/28/2020
MultiMBNN: Matched and Balanced Causal Inference with Neural Networks
Causal inference (CI) in observational studies has received a lot of att...
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04/28/2020
Privacy Guidelines for Contact Tracing Applications
Contact tracing is a very powerful method to implement and enforce socia...
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12/09/2019
MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population
Performing inference on data obtained through observational studies is b...
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09/13/2019
Meta-Learning for Few-Shot Time Series Classification
Deep neural networks (DNNs) have achieved state-of-the-art results on ti...
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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...
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07/16/2019
Meta-Learning for Black-box Optimization
Recently, neural networks trained as optimizers under the "learning to l...
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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...
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05/31/2019
Fast Online "Next Best Offers" using Deep Learning
In this paper, we present iPrescribe, a scalable low-latency architectur...
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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...
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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...
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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 ...
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12/28/2018
MEETING BOT: Reinforcement Learning for Dialogue Based Meeting Scheduling
In this paper we present Meeting Bot, a reinforcement learning based con...
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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...
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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...
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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...
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10/25/2017
Crop Planning using Stochastic Visual Optimization
As the world population increases and arable land decreases, it becomes ...
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08/18/2017
Comparative Benchmarking of Causal Discovery Techniques
In this paper we present a comprehensive view of prominent causal discov...
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12/20/2016
Neuro-symbolic EDA-based Optimisation using ILP-enhanced DBNs
We investigate solving discrete optimisation problems using the estimati...
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08/03/2016
Generation of Near-Optimal Solutions Using ILP-Guided Sampling
Our interest in this paper is in optimisation problems that are intracta...
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07/01/2016
LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection
Mechanical devices such as engines, vehicles, aircrafts, etc., are typic...
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11/11/2014