| AxFormer: Accuracy-driven approximation of transformers for faster, smaller and more accurate NLP models A Nagarajan, S Sen, JR Stevens, A Raghunathan 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 8* | 2022 |
| Efficient ensembles of graph neural networks A Nagarajan, JR Stevens, A Raghunathan Proceedings of the 59th ACM/IEEE Design Automation Conference, 187-192, 2022 | 7 | 2022 |
| Fastrain-gnn: Fast and accurate self-training for graph neural networks A Nagarajan, A Raghunathan Transactions on Machine Learning Research, 2023 | 1 | 2023 |
| Optimizing Accuracy-Efficiency Tradeoffs in Emerging Neural Workloads A Nagarajan Purdue University Graduate School, 2023 | | 2023 |
| TokenDrop+ BucketSampler: Towards Efficient Padding-free Fine-tuning of Language Models A Nagarajan, A Raghunathan The 2023 Conference on Empirical Methods in Natural Language Processing, 2023 | | 2023 |
| Input Compression with Positional Consistency for Efficient Training and Inference of Transformer Neural Networks A Nagarajan, A Raghunathan arXiv preprint arXiv:2312.12385, 2023 | | 2023 |
Anand RaghunathanProfessor of Electrical and Computer Engineering, Purdue UniversityVerified email at purdue.edu
