79 citations · 495 across the 38 of their papers we have counts for
19 papers · 1 filter
Exploring Vicinal Risk Minimization for Lightweight Out-of-Distribution Detection
Deepak Ravikumar, Sangamesh Kodge, Isha Garg +1
Deep neural networks have found widespread adoption in solving complex tasks ranging from image recognition to natural language processing. However, these networks make confident m…
DCT-SNN: Using DCT to Distribute Spatial Information over Time for Learning Low-Latency Spiking Neural Networks
Isha Garg, Sayeed Shafayet Chowdhury, Kaushik Roy
Spiking Neural Networks (SNNs) offer a promising alternative to traditional deep learning frameworks, since they provide higher computational efficiency due to event-driven informa…
On the Intrinsic Robustness of NVM Crossbars Against Adversarial Attacks
Deboleena Roy, Indranil Chakraborty, Timur Ibrayev +1
The increasing computational demand of Deep Learning has propelled research in special-purpose inference accelerators based on emerging non-volatile memory (NVM) technologies. Such…
DIET-SNN: Direct Input Encoding With Leakage and Threshold Optimization in Deep Spiking Neural Networks
Nitin Rathi, Kaushik Roy
Bio-inspired spiking neural networks (SNNs), operating with asynchronous binary signals (or spikes) distributed over time, can potentially lead to greater computational efficiency…
TREND: Transferability based Robust ENsemble Design
Deepak Ravikumar, Sangamesh Kodge, Isha Garg +1
Deep Learning models hold state-of-the-art performance in many fields, but their vulnerability to adversarial examples poses threat to their ubiquitous deployment in practical sett…
Towards Understanding the Effect of Leak in Spiking Neural Networks
Sayeed Shafayet Chowdhury, Chankyu Lee, Kaushik Roy
Spiking Neural Networks (SNNs) are being explored to emulate the astounding capabilities of human brain that can learn and compute functions robustly and efficiently with noisy spi…