5 papers
GradAttn: Replacing Fixed Residual Connections with Task-Modulated Attention Pathways
Soudeep Ghoshal, Himanshu Buckchash
Deep ConvNets suffer from gradient signal degradation as network depth increases, limiting effective feature learning in complex architectures. ResNet addressed this through residu…
Fusing Memory and Attention: A study on LSTM, Transformer and Hybrid Architectures for Symbolic Music Generation
Soudeep Ghoshal, Sandipan Chakraborty, Pradipto Chowdhury +1
Machine learning techniques, such as Transformers and Long Short-Term Memory (LSTM) networks, play a crucial role in Symbolic Music Generation (SMG). Existing literature indicates…
NDT: Non-Differential Transformer and Its Application to Sentiment Analysis
Soudeep Ghoshal, Himanshu Buckchash, Sarita Paudel +1
From customer feedback to social media, understanding human sentiment in text is central to how machines can interact meaningfully with people. However, despite notable progress, a…
Applications and Challenges of AI and Microscopy in Life Science Research: A Review
Himanshu Buckchash, Gyanendra Kumar Verma, Dilip K. Prasad
The complexity of human biology and its intricate systems holds immense potential for advancing human health, disease treatment, and scientific discovery. However, traditional manu…
Hedging Is Not All You Need: A Simple Baseline for Online Learning Under Haphazard Inputs
Himanshu Buckchash, Momojit Biswas, Rohit Agarwal +1
Handling haphazard streaming data, such as data from edge devices, presents a challenging problem. Over time, the incoming data becomes inconsistent, with missing, faulty, or new i…