activity
20192024
most citedATM Cash demand forecasting in an Indian Bank with chaos and deep learning

26 citations · 80 across the 29 of their papers we have counts for

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Showing 2022Show all

12 papers · 1 filter

cs.LG2022★ 3 cited

Chaotic Variational Auto Encoder based One Class Classifier for Insurance Fraud Detection

K. S. N. V. K. Gangadhar, B. Akhil Kumar, Yelleti Vivek +1

Of late, insurance fraud detection has assumed immense significance owing to the huge financial & reputational losses fraud entails and the phenomenal success of the fraud detectio…

cs.LG2022★ 2 cited

Explainable Artificial Intelligence and Causal Inference based ATM Fraud Detection

Yelleti Vivek, Vadlamani Ravi, Abhay Anand Mane +1

Gaining the trust of customers and providing them empathy are very critical in the financial domain. Frequent occurrence of fraudulent activities affects these two factors. Hence,…

cs.NE2022

Parallel and Streaming Wavelet Neural Networks for Classification and Regression under Apache Spark

Eduru Harindra Venkatesh, Yelleti Vivek, Vadlamani Ravi +1

Wavelet neural networks (WNN) have been applied in many fields to solve regression as well as classification problems. After the advent of big data, as data gets generated at a bri…

cs.LG2022★ 1 cited

Application of Causal Inference to Analytical Customer Relationship Management in Banking and Insurance

Satyam Kumar, Vadlamani Ravi

Of late, in order to have better acceptability among various domain, researchers have argued that machine intelligence algorithms must be able to provide explanations that humans c…

cs.AI2022★ 5 cited

Explainable Reinforcement Learning on Financial Stock Trading using SHAP

Satyam Kumar, Mendhikar Vishal, Vadlamani Ravi

Explainable Artificial Intelligence (XAI) research gained prominence in recent years in response to the demand for greater transparency and trust in AI from the user communities. T…

cs.LG2022★ 1 cited

Privacy-Preserving Chaotic Extreme Learning Machine with Fully Homomorphic Encryption

Syed Imtiaz Ahamed, Vadlamani Ravi

The Machine Learning and Deep Learning Models require a lot of data for the training process, and in some scenarios, there might be some sensitive data, such as customer informatio…