Gaurav Dhama

According to our database, Gaurav Dhama authored at least 18 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

Fraud Type Decomposition and the Observation-Mechanism Taxonomy:Class-Specific Detection Limits in Payment Networks.

Gaurav Dhama

CoRR, May, 2026

Causal Label Recovery in Payment Networks.

Gaurav Dhama

CoRR, May, 2026

The Fundamental Limits of Fraud Detection in Card Payment Networks.

Gaurav Dhama

CoRR, May, 2026

2023

FraudAmmo: Large Scale Synthetic Transactional Dataset for Payment Fraud Detection.

Karthikeswaren Ramachandran, Kanishka Kayathwal, Hardik Wadhwa, Gaurav Dhama

Proceedings of the International Joint Conference on Neural Networks, 2023

TETRAA - Trained and Selective Transmutation of Encoder-based Adversarial Attack.

Sarthak Malik, Himanshi Charotia, Gaurav Dhama

Proceedings of the International Joint Conference on Neural Networks, 2023

2022

Entity Alignment For Knowledge Graphs: Progress, Challenges, and Empirical Studies.

Deepak Chaurasiya, Anil Surisetty, Nitish Kumar, Alok Singh, Vikrant Dey, Aakarsh Malhotra, Gaurav Dhama, Ankur Arora

CoRR, 2022

Dynamic Temporal Reconciliation by Reinforcement learning.

Himanshi Charotia, Abhishek Garg, Gaurav Dhama, Naman Maheshwari

CoRR, 2022

RePS: Relation, Position and Structure aware Entity Alignment.

Anil Surisetty, Deepak Chaurasiya, Nitish Kumar, Alok Singh, Gaurav Dhama, Aakarsh Malhotra, Ankur Arora, Vikrant Dey

Proceedings of the Companion of The Web Conference 2022, Virtual Event / Lyon, France, April 25, 2022

2021

Optimal Latent Space Forecasting for Large Collections of Short Time Series Using Temporal Matrix Factorization.

Himanshi Charotia, Abhishek Garg, Gaurav Dhama, Naman Maheshwari

CoRR, 2021

Application of Deep Reinforcement Learning to Payment Fraud.

Siddharth Vimal, Kanishka Kayathwal, Hardik Wadhwa, Gaurav Dhama

CoRR, 2021

KARL-Trans-NER: Knowledge Aware Representation Learning for Named Entity Recognition using Transformers.

Avi Chawla, Nidhi Mulay, Vikas Bishnoi, Gaurav Dhama

CoRR, 2021

A Survey on Classical and Deep Learning based Intermittent Time Series Forecasting Methods.

Karthikeswaren R, Kanishka Kayathwal, Gaurav Dhama, Ankur Arora

Proceedings of the International Joint Conference on Neural Networks, 2021

MeTGAN: Memory Efficient Tabular GAN for High Cardinality Categorical Datasets.

Shreyansh Singh, Kanishka Kayathwal, Hardik Wadhwa, Gaurav Dhama

Proceedings of the Neural Information Processing - 28th International Conference, 2021

A Comparative Study of Transformers on Word Sense Disambiguation.

Avi Chawla, Nidhi Mulay, Vikas Bishnoi, Gaurav Dhama, Anil Kumar Singh

Proceedings of the Neural Information Processing - 28th International Conference, 2021

Evolutionary Adversarial Attacks on Payment Systems.

Nishant Kumar, Siddharth Vimal, Kanishka Kayathwal, Gaurav Dhama

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

Improving the performance of Transformer Context Encoders for NER.

Avi Chawla, Nidhi Mulay, Vikas Bishnoi, Gaurav Dhama

Proceedings of the 24th IEEE International Conference on Information Fusion, 2021

2020

Pandemic spread prediction and healthcare preparedness through financial and mobility data.

Nidhi Mulay, Vikas Bishnoi, Himanshi Charotia, Siddhartha Asthana, Gaurav Dhama, Ankur Arora

Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020

Deep Learning based Time Series Forecasting.

Kushagra Agarwal, Lalasa Dheekollu, Gaurav Dhama, Ankur Arora, Siddhartha Asthana, Tanmoy Bhowmik

Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020