Optimizing Transformers with Approximate Computing for Faster, Smaller and more Accurate NLP Models. - Amrit Nagarajan; Sanchari Sen; Jacob R. Stevens; Anand Raghunathan (CoRR, 2020)

Efficient ensembles of graph neural networks. - Amrit Nagarajan; Jacob R. Stevens; Anand Raghunathan (DAC, 2022)

AxFormer: Accuracy-driven Approximation of Transformers for Faster, Smaller and more Accurate NLP Models. - Amrit Nagarajan; Sanchari Sen; Jacob R. Stevens; Anand Raghunathan (IJCNN, 2022)

TokenDrop + BucketSampler: Towards Efficient Padding-free Fine-tuning of Language Models. - Amrit Nagarajan; Anand Raghunathan (EMNLP (Findings), 2023)

FASTRAIN-GNN: Fast and Accurate Self-Training for Graph Neural Networks. - Amrit Nagarajan; Anand Raghunathan (Trans. Mach. Learn. Res., 2023)

Input Compression with Positional Consistency for Efficient Training and Inference of Transformer Neural Networks. - Amrit Nagarajan; Anand Raghunathan (ECML/PKDD (5), 2024)

Efficient Batched Inference in Conditional Neural Networks. - Surya Selvam; Amrit Nagarajan; Anand Raghunathan (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)