97 citations · 110 across the 5 of their papers we have counts for
5 papers
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers
Md Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian
Graph transformers typically lack third-order interactions, limiting their geometric understanding which is crucial for tasks like molecular geometry prediction. We propose the Tri…
The Information Pathways Hypothesis: Transformers are Dynamic Self-Ensembles
Md Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian
Transformers use the dense self-attention mechanism which gives a lot of flexibility for long-range connectivity. Over multiple layers of a deep transformer, the number of possible…
Global Self-Attention as a Replacement for Graph Convolution
Md Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian
We propose an extension to the transformer neural network architecture for general-purpose graph learning by adding a dedicated pathway for pairwise structural information, called…
An Improved Physics Based Numerical Model of Tunnel FET Using 2D NEGF Formalism
Md Shamim Hussain
In this work, we have investigated a 2D model of band-to-band tunneling based on 2-band model and implemented it using 2D NEGF formalism. Being 2D in nature, this model better addr…
SwishNet: A Fast Convolutional Neural Network for Speech, Music and Noise Classification and Segmentation
Md. Shamim Hussain, Mohammad Ariful Haque
Speech, Music and Noise classification/segmentation is an important preprocessing step for audio processing/indexing. To this end, we propose a novel 1D Convolutional Neural Networ…