| Perceiver io: A general architecture for structured inputs & outputs A Jaegle, S Borgeaud, JB Alayrac, C Doersch, C Ionescu, D Ding, ... arXiv preprint arXiv:2107.14795, 2021 | 667 | 2021 |
| Efficient visual pretraining with contrastive detection OJ Hénaff, S Koppula, JB Alayrac, A Van den Oord, O Vinyals, J Carreira Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 185 | 2021 |
| EDEN: Enabling Energy-Efficient, High-Performance Deep Neural Network Inference Using Approximate DRAM S Koppula, L Orosa, AG Yağlıkçı, R Azizi, T Shahroodi, K Kanellopoulos, ... Proceedings of the 52nd Annual IEEE/ACM International Symposium on …, 2019 | 154 | 2019 |
| Paligemma: A versatile 3b vlm for transfer L Beyer, A Steiner, AS Pinto, A Kolesnikov, X Wang, D Salz, M Neumann, ... arXiv preprint arXiv:2407.07726, 2024 | 147 | 2024 |
| SMASH: Co-designing software compression and hardware-accelerated indexing for efficient sparse matrix operations K Kanellopoulos, N Vijaykumar, C Giannoula, R Azizi, S Koppula, ... Proceedings of the 52nd Annual IEEE/ACM International Symposium on …, 2019 | 118 | 2019 |
| Perception test: A diagnostic benchmark for multimodal video models V Patraucean, L Smaira, A Gupta, A Recasens, L Markeeva, D Banarse, ... Advances in Neural Information Processing Systems 36, 42748-42761, 2023 | 106 | 2023 |
| Object discovery and representation networks OJ Hénaff, S Koppula, E Shelhamer, D Zoran, A Jaegle, A Zisserman, ... European Conference on Computer Vision, 123-143, 2022 | 99 | 2022 |
| Lossless adaptation of pretrained vision models for robotic manipulation M Sharma, C Fantacci, Y Zhou, S Koppula, N Heess, J Scholz, Y Aytar arXiv preprint arXiv:2304.06600, 2023 | 31 | 2023 |
| Accurate, low-latency visual perception for autonomous racing: Challenges, mechanisms, and practical solutions K Strobel, S Zhu, R Chang, S Koppula 2020 IEEE/RSJ international conference on intelligent robots and systems …, 2020 | 29 | 2020 |
| Hip: Hierarchical perceiver J Carreira, S Koppula, D Zoran, A Recasens, C Ionescu, O Henaff, ... arXiv preprint arXiv:2202.10890, 2022 | 28 | 2022 |
| Power-based Side-Channel Attack for AES Key Extraction on the ATmega328 Microcontroller U Banerjee, L Ho, S Koppula Computer Systems Security, 2015 | 23* | 2015 |
| A simple recipe for contrastively pre-training video-first encoders beyond 16 frames P Papalampidi, S Koppula, S Pathak, J Chiu, J Heyward, V Patraucean, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 22 | 2024 |
| Memory consolidation enables long-context video understanding I Balažević, Y Shi, P Papalampidi, R Chaabouni, S Koppula, OJ Hénaff arXiv preprint arXiv:2402.05861, 2024 | 19 | 2024 |
| Bootstap: Bootstrapped training for tracking-any-point C Doersch, P Luc, Y Yang, D Gokay, S Koppula, A Gupta, J Heyward, ... Proceedings of the Asian Conference on Computer Vision, 3257-3274, 2024 | 18 | 2024 |
| Paligemma: A versatile 3b vlm for transfer, 2024 L Beyer, A Steiner, AS Pinto, A Kolesnikov, X Wang, D Salz, M Neumann, ... URL https://arxiv. org/abs/2407.07726, 0 | 17 | |
| Where should i spend my flops? efficiency evaluations of visual pre-training methods S Koppula, Y Li, E Shelhamer, A Jaegle, N Parthasarathy, R Arandjelovic, ... arXiv preprint arXiv:2209.15589, 2022 | 12 | 2022 |
| Applying the Residue Number System to Neural Network Inference M Abdelhamid, S Koppula arXiv preprint arXiv:1712.04614, 2017 | 12 | 2017 |
| Learning a CNN-based End-to-end Controller for a Formula SAE Racecar S Koppula arXiv preprint arXiv:1708.02215, 2017 | 7 | 2017 |
| Tapvid-3d: A benchmark for tracking any point in 3d S Koppula, I Rocco, Y Yang, J Heyward, J Carreira, A Zisserman, ... arXiv preprint arXiv:2407.05921, 2024 | 5 | 2024 |
| Energy-efficient speaker identification with low-precision networks S Koppula, J Glass, AP Chandrakasan 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 5 | 2018 |
Utsav BanerjeeIndian Institute of ScienceEmail được xác minh tại alum.mit.edu