Super-naturalinstructions: Generalization via declarative instructions on 1600+ nlp tasks Y Wang, S Mishra, P Alipoormolabashi, Y Kordi, A Mirzaei, A Arunkumar, ... arXiv preprint arXiv:2204.07705, 2022 | 659* | 2022 |
Lag-Llama: Towards Foundation Models for Time Series Forecasting K Rasul*, A Ashok*, AR Williams, A Khorasani, G Adamopoulos, ... arXiv preprint arXiv:2310.08278, 2023 | 159* | 2023 |
Extremely Simple Activation Shaping for Out-of-Distribution Detection A Djurisic, N Bozanic, A Ashok, R Liu ICLR, 2023 | 156 | 2023 |
Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer A Ashok, KJ Joseph, V Balasubramanian ECCV, 2022 | 33 | 2022 |
TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series A Ashok, É Marcotte, V Zantedeschi, N Chapados, A Drouin ICLR, 2024 | 14 | 2024 |
Context is Key: A Benchmark for Forecasting with Essential Textual Information AR Williams*, A Ashok*, É Marcotte, V Zantedeschi, J Subramanian, ... arXiv preprint arXiv:2410.18959, 2024 | 2 | 2024 |
[Re] Does Self-Supervision Always Improve Few-Shot Learning? A Ashok, H Aekula ML Reproducibility Challenge 2021 (Fall Edition), 2022 | 1* | 2022 |
Learning Modular Structures That Generalize Out-of-Distribution A Ashok, C Devaguptapu, VN Balasubramanian AAAI, 2022 | 1* | 2022 |