Estimation of SNM in latches and subsequent formation of a 10T CNFET bitcell. - Isha Garg; Prakhar Sharma (WISES, 2013)

On-the-Fly Donut Formation in Compiled Memory. - Darvinder Singh; Isha Garg; Vineet Sachan; Prasanna Nalawar (VLSID, 2015)

PCA-driven Hybrid network design for enabling Intelligence at the Edge. - Indranil Chakraborty; Deboleena Roy; Isha Garg; Aayush Ankit; Kaushik Roy 001 (CoRR, 2019)

A Low Effort Approach to Structured CNN Design Using PCA. - Isha Garg; Priyadarshini Panda; Kaushik Roy 001 (IEEE Access, 2020)

Structured Compression and Sharing of Representational Space for Continual Learning. - Gobinda Saha; Isha Garg; Aayush Ankit; Kaushik Roy 001 (CoRR, 2020)

DCT-SNN: Using DCT to Distribute Spatial Information over Time for Learning Low-Latency Spiking Neural Networks. - Isha Garg; Sayeed Shafayet Chowdhury; Kaushik Roy 001 (CoRR, 2020)

Exploring Vicinal Risk Minimization for Lightweight Out-of-Distribution Detection. - Deepak Ravikumar; Sangamesh Kodge; Isha Garg; Kaushik Roy 001 (CoRR, 2020)

Constructing energy-efficient mixed-precision neural networks through principal component analysis for edge intelligence. - Indranil Chakraborty; Deboleena Roy; Isha Garg; Aayush Ankit; Kaushik Roy 001 (Nat. Mach. Intell., 2020)

DCT-SNN: Using DCT to Distribute Spatial Information over Time for Low-Latency Spiking Neural Networks. - Isha Garg; Sayeed Shafayet Chowdhury; Kaushik Roy 001 (ICCV, 2021)

Gradient Projection Memory for Continual Learning. - Gobinda Saha; Isha Garg; Kaushik Roy 001 (ICLR, 2021)

Spatio-Temporal Pruning and Quantization for Low-latency Spiking Neural Networks. - Sayeed Shafayet Chowdhury; Isha Garg; Kaushik Roy 001 (IJCNN, 2021)

SPACE: Structured Compression and Sharing of Representational Space for Continual Learning. - Gobinda Saha; Isha Garg; Aayush Ankit; Kaushik Roy 001 (IEEE Access, 2021)

TOFU: Towards Obfuscated Federated Updates by Encoding Weight Updates into Gradients from Proxy Data. - Isha Garg; Manish Nagaraj; Kaushik Roy 001 (CoRR, 2022)

Samples with Low Loss Curvature Improve Data Efficiency. - Isha Garg; Kaushik Roy 001 (CVPR, 2023)

Intra-Class Mixup for Out-of-Distribution Detection. - Deepak Ravikumar; Sangamesh Kodge; Isha Garg; Kaushik Roy 001 (IEEE Access, 2023)

Memorization Through the Lens of Curvature of Loss Function Around Samples. - Isha Garg; Kaushik Roy 001 (CoRR, 2023)

TREND: Transferability-Based Robust ENsemble Design. - Deepak Ravikumar; Sangamesh Kodge; Isha Garg; Kaushik Roy 001 (IEEE Trans. Artif. Intell., 2023)

Memorization Through the Lens of Curvature of Loss Function Around Samples. - Isha Garg; Deepak Ravikumar; Kaushik Roy 001 (ICML, 2024)

TOFU: Toward Obfuscated Federated Updates by Encoding Weight Updates Into Gradients From Proxy Data. - Manish Nagaraj; Isha Garg; Kaushik Roy 001 (IEEE Access, 2024)

Pruning for Improved ADC Efficiency in Crossbar-based Analog In-memory Accelerators. - Timur Ibrayev; Isha Garg; Indranil Chakraborty; Kaushik Roy 001 (CoRR, 2024)

Encoding Hierarchical Information in Neural Networks Helps in Subpopulation Shift. - Amitangshu Mukherjee; Isha Garg; Kaushik Roy 001 (IEEE Trans. Artif. Intell., 2024)

Revealing the Utilized Rank of Subspaces of Learning in Neural Networks. - Isha Garg; Christian Koguchi; Eshan Verma; Daniel Ulbricht (AAAI Spring Symposia, 2025)