• Information fusion using convolutional transform learning 

  Gupta, Pooja; Majumdar, Angshul (Advisor) (IIIT-Delhi, 2023-09)

  There are many real-world problems pertaining to the need for the fusion of information from multiple sources. Consider, for example, the problem of demand forecasting that requires estimating the power consumption at a ...
• A study on smooth activation functions 

  Biswas, Koushik; Pandey, Ashish Kumar (Advisor); Banerjee, Shilpak (Advisor) (IIIT-Delhi, 2023-07)

  Artificial neural networks (ANNs) have occupied the centre stage in deep learning. An activation function is a crucial component in the neural network, which introduces the non-linearity in the network. An activation ...
• Finding unique pattern in transcriptome and epigenome of cancer cells 

  Mathur, Arpit; Kumar, Vibhor (Advisor) (IIIT-Delhi, 2022-12)

  Studying Chromatin Architecture is paramount to an understanding of cells or nuclei in disease and normal state. With recent advances in genomic technologies and computational power, new domains like Topologically associated ...
• Learning content curation and enrichment 

  V, Venktesh; Mohania, Mukesh (Advisor); Goyal, Vikram (Advisor) (IIIT-Delhi, 2023-03)

  Education in traditional classroom settings was restricted to static content in textbooks. It also assumes all the learners have a similar pace of learning. Online learning platforms have shifted the paradigm and have made ...
• Advancing graph-based computational approaches to decipher omic signature of diseases 

  Mishra, Shreya; Kumar, Vibhor (Advisor) (IIIT-Delhi, 2022-10-31)

  Omic signatures of disease are important for personalized treatment because of theheterogeneity of diseases. Despite the advancement of computational tools, there arelimited methods that can capture the latent inter-relationships ...

View more