13 citations · 15 across the 11 of their papers we have counts for
5 papers · 1 filter
Dynamic Long-Term Time-Series Forecasting via Meta Transformer Networks
Muhammad Anwar Ma'sum, MD Rasel Sarkar, Mahardhika Pratama +5
A reliable long-term time-series forecaster is highly demanded in practice but comes across many challenges such as low computational and memory footprints as well as robustness ag…
Scalable Adversarial Online Continual Learning
Tanmoy Dam, Mahardhika Pratama, MD Meftahul Ferdaus +2
Adversarial continual learning is effective for continual learning problems because of the presence of feature alignment process generating task-invariant features having low susce…
Latent Preserving Generative Adversarial Network for Imbalance classification
Tanmoy Dam, Md Meftahul Ferdaus, Mahardhika Pratama +3
Many real-world classification problems have imbalanced frequency of class labels; a well-known issue known as the "class imbalance" problem. Classic classification algorithms tend…
Does Adversarial Oversampling Help us?
Tanmoy Dam, Md Meftahul Ferdaus, Sreenatha G. Anavatti +2
Traditional oversampling methods are generally employed to handle class imbalance in datasets. This oversampling approach is independent of the classifier; thus, it does not offer…
Improving ClusterGAN Using Self-Augmented Information Maximization of Disentangling Latent Spaces
Tanmoy Dam, Sreenatha G. Anavatti, Hussein A. Abbass
Since their introduction in the last few years, conditional generative models have seen remarkable achievements. However, they often need the use of large amounts of labelled infor…