| FastGRNN: A Fast, accurate, stable & tiny kilobyte sized Gated Recurrent Neural Network A Kusupati, M Singh, K Bhatia, A Kumar, P Jain, M Varma NeurIPS 2018, 2018 | 225 | 2018 |
| MERLOT Reserve: Neural Script Knowledge through Vision and Language and Sound R Zellers, J Lu, X Lu, Y Yu, Y Zhao, M Salehi, A Kusupati, J Hessel, ... CVPR 2022, 2022 | 208 | 2022 |
| Soft Threshold Weight Reparameterization for Learnable Sparsity A Kusupati, V Ramanujan, R Somani, M Wortsman, P Jain, S Kakade, ... ICML 2020, 2020 | 208 | 2020 |
| Objaverse-xl: A universe of 10m+ 3d objects M Deitke, R Liu, M Wallingford, H Ngo, O Michel, A Kusupati, A Fan, ... NeurIPS Datasets & Benchmarks 2023, 2023 | 137 | 2023 |
| RNNPool: Efficient Non-linear Pooling for RAM Constrained Inference O Saha, A Kusupati, HV Simhadri, M Varma, P Jain NeurIPS 2020, 2020 | 56 | 2020 |
| EdgeML: Machine Learning for resource-constrained edge devices DK Dennis, Y Gaurkar, S Gopinath, S Goyal, C Gupta, M Jain, A Kumar, ... https://github.com/microsoft/EdgeML, 2017 | 43* | 2017 |
| Matryoshka Representation Learning A Kusupati, G Bhatt, A Rege, M Wallingford, A Sinha, V Ramanujan, ... NeurIPS 2022, 2022 | 38* | 2022 |
| MADLAD-400: A Multilingual And Document-Level Large Audited Dataset S Kudugunta, I Caswell, B Zhang, X Garcia, CA Choquette-Choo, K Lee, ... NeurIPS Datasets & Benchmarks 2023, 2023 | 31 | 2023 |
| One size does not fit all: Multi-scale, cascaded RNNs for radar classification D Roy, S Srivastava, A Kusupati, P Jain, M Varma, A Arora BuildSys 2019 (Best Paper Runner-Up), 2019 | 26* | 2019 |
| Extreme Regression for Dynamic Search Advertising Y Prabhu, A Kusupati, N Gupta, M Varma WSDM 2020, 2020 | 23 | 2020 |
| ProtoSound: A Personalized and Scalable Sound Recognition System for Deaf and Hard of Hearing Users D Jain, KHA Nguyen, S Goodman, R Grossman-Kahn, H Ngo, A Kusupati, ... CHI 2022, 2022 | 21* | 2022 |
| Efficient Spatial Representation for Entity-Typing A Kusupati, A Dhoot, S Chakrabarti Bachelor Thesis Report, IIT Bombay, 2017 | 18* | 2017 |
| FLUID: A Unified Evaluation Framework for Flexible Sequential Data. M Wallingford, A Kusupati, K Alizadeh-Vahid, A Walsman, A Kembhavi, ... TMLR 2023, 2023 | 13* | 2023 |
| LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes A Kusupati, M Wallingford, V Ramanujan, R Somani, JS Park, K Pillutla, ... NeurIPS 2021, 2021 | 11 | 2021 |
| Disrupting Model Training with Adversarial Shortcuts I Evtimov, I Covert, A Kusupati, T Kohno Workshop on Adversarial Machine Learning @ ICML 2021, 2021 | 9 | 2021 |
| Gecko: Versatile text embeddings distilled from large language models J Lee, Z Dai, X Ren, B Chen, D Cer, JR Cole, K Hui, M Boratko, ... arXiv preprint arXiv:2403.20327, 2024 | 7 | 2024 |
| Neural Priming for Sample-Efficient Adaptation M Wallingford, V Ramanujan, A Fang, A Kusupati, R Mottaghi, ... NeurIPS 2023, 2023 | 7 | 2023 |
| Neural Radiance Field Codebooks M Wallingford, A Kusupati, A Fang, V Ramanujan, A Kembhavi, ... ICLR 2023, 2023 | 5 | 2023 |
| MatFormer: Nested Transformer for Elastic Inference Devvrit*, S Kudugunta*, A Kusupati*, T Dettmers, K Chen, I Dhillon, ... arXiv preprint arXiv:2310.07707, 2023 | 4* | 2023 |
| SHARCS: Efficient transformers through routing with dynamic width sub-networks M Salehi, S Mehta, A Kusupati, A Farhadi, H Hajishirzi EMNLP Findings 2023, 2023 | 3 | 2023 |
Ali FarhadiProfessor, Computer Science and Engineering, University of Washington在 cs.uw.edu 的电子邮件经过验证
