A simple and efficient SNN and its performance & robustness evaluation method to enable hardware implementation. - Anmol Biswas; Sidharth Prasad; Sandip Lashkare; Udayan Ganguly (CoRR, 2016)

Spatially Variant Laplacian Pyramids for Multi-frame Exposure Fusion. - Anmol Biswas; Green Rosh K. S; Sachin Deepak Lomte (CVIP (1), 2019)

Deep Multi-Stage Learning for HDR With Large Object Motions. - Green Rosh K. S; Anmol Biswas; Mandakinee Singh Patel; B. H. Pawan Prasad (ICIP, 2019)

Fast Multi-Stage Motion-Compensated Approach for HDR. - Anmol Biswas; Green Rosh K. S; Mandakinee Singh Patel; B. H. Pawan Prasad (ICIP, 2020)

MAdapter: A Multimodal Adapter for Liquid State Machines configures the Input Layer for the same Reservoir to enable Vision and Speech Classification. - Anmol Biswas; Nivedya S. Nambiar; Kushal Kejriwal; Udayan Ganguly (IJCNN, 2023)

Real-world Performance Estimation of Liquid State Machines for Spoken Digit Classification. - Abhishek Kadam; Anmol Biswas; Vivek Saraswat; Ajay Kumar Singh; Laxmeesha Somappa; Maryam Shojaei Baghini; Udayan Ganguly (IJCNN, 2023)

E-STDP: A Spatio-Temporally Local Unsupervised Learning Rule for Sparse Coded Spiking Convolutional Autoencoders. - Vineet Kotariya; Anmol Biswas; Udayan Ganguly (IJCNN, 2023)

Schottky Barrier MOSFET Enabled Ultra-Low Power Real-Time Neuron for Neuromorphic Computing. - Shubham Patil; Jayatika Sakhuja; Ajay Kumar Singh; Anmol Biswas; Vivek Saraswat; Sandeep Kumar; Sandip Lashkare; Udayan Ganguly (CoRR, 2023)

A temporally and spatially local spike-based backpropagation algorithm to enable training in hardware. - Anmol Biswas; Vivek Saraswat; Udayan Ganguly (Neuromorph. Comput. Eng., 2023)

Resistive Processing Unit-based On-chip ANN Training with Digital Memory. - Shreyas Deshmukh; Shubham Patil; Anmol Biswas; Vivek Saraswat; Abhishek Kadam; Ajay Kumar Singh; Laxmeesha Somappa; Maryam Shojaei Baghini; Udayan Ganguly (AICAS, 2024)

Temporal and Spatial Reservoir Ensembling Techniques for Liquid State Machines. - Anmol Biswas; Sharvari Ashok Medhe; Raghav Singhal; Udayan Ganguly (ICONS, 2024)

QFALT: Quantization and Fault Aware Loss for Training Enables Performance Recovery with Unreliable Weights. - Anmol Biswas; Udayan Ganguly (IJCNN, 2024)

Area Efficient Multi-Memristor Bit Cell Design for Resistive Processing Unit-Based Neural Network Training. - Gaurav R; Ujwal Uttarwar; Shreyas Deshmukh; Jayatika Sakhuja; Kunal Randad; Samarth Agarwal; Akshata Koshti; Anmol Biswas; Udayan Ganguly (NVMTS, 2024)

System-level Impact of Non-Ideal Program-Time of Charge Trap Flash (CTF) on Deep Neural Network. - Shalini Shrivastava; Anmol Biswas; Samyak Chakrabarty; Gayatri Dash; Vivek Saraswat; Udayan Ganguly (CoRR, 2024)

Regularization-based Framework for Quantization-, Fault- and Variability-Aware Training. - Anmol Biswas; Raghav Singhal; Sivakumar Elangovan; Shreyas Sabnis; Udayan Ganguly (CoRR, 2025)