Abhimanyu Das
Artificial Intelligence · 2011–2023
A researcher in the Science corpus: 6 papers; trusts 39 researchers and is trusted by 35 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 36 citations into it
- Management Science and Operations Research — 32 citations into it
- Signal Processing — 31 citations into it
- Computational Mechanics — 12 citations into it; #1,210 of 10,001 by trust here, #2,644 by citations
- Computer Vision and Pattern Recognition — 12 citations into it; #4,889 of 21,575 by trust here, #10,334 by citations
- Optimization & Training — 9 citations into it; #728 of 2,601 by trust here, #1,585 by citations
- Time-Series & Forecasting — 9 citations into it
- Statistics and Probability — 8 citations into it; #7,811 of 12,932 by trust here, #8,740 by citations
Whom Abhimanyu Das trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Tong Zhang
- Robert Tibshirani
- Ed McKenzie
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Smola
- Alex Krizhevsky
- Valentin Flunkert
- Ilya Sutskever
Who trusts Abhimanyu Das overall
- Krishnateja Killamsetty
- Karthik S. Gurumoorthy
- Sharon Qian
- Alexander Grubb
- Christian Hansen
- Ethan R. Elenberg
- Christopher Harshaw
- Yatao Bian
- Yu Zhang
- Amit Dhurandhar
Papers from Abhimanyu Das's perspective
Ordered by how strongly the researchers Abhimanyu Das trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection (2011) — 517 citations
- Scalable hierarchical multitask learning algorithms for conversion optimization in display advertising (2014) — 42 citations
- A decoder-only foundation model for time-series forecasting (2023) — 785 citations
- Web-scale multi-task feature selection for behavioral targeting (2012) — 11 citations
- Debiasing social wisdom (2013) — 58 citations
- Long-term Forecasting with TiDE: Time-series Dense Encoder (2023) — 600 citations