Anshuman Tripathi
Artificial Intelligence · 2018–2020
A researcher in the Science corpus: 4 papers; trusts 27 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 81 citations into it; #21,424 of 35,345 by trust here, #11,750 by citations
- Signal Processing — 58 citations into it; #5,817 of 7,572 by trust here, #1,783 by citations
- Speech & Audio — 42 citations into it; #685 of 1,076 by trust here, #472 by citations
- Model Architectures — 18 citations into it; #2,086 of 2,278 by trust here, #1,343 by citations
- Computer Vision and Pattern Recognition — 10 citations into it
- Optimization & Training — 6 citations into it
Whom Anshuman Tripathi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Graves
- Jimmy Ba
- Diederik P. Kingma
- Geoffrey E. Hinton
- Hasim Sak
- Yoshua Bengio
- Dzmitry Bahdanau
- Andrew W. Senior
- J. Urgen Schmidhuber
- Alex Krizhevsky
Who trusts Anshuman Tripathi overall
Papers from Anshuman Tripathi's perspective
Ordered by how strongly the researchers Anshuman Tripathi trusts endorse each paper. Same corpus, a different order for every researcher.
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Transformer Transducer: A Streamable Speech Recognition Model with Transformer Encoders and RNN-T Loss (2020) — 539 citations
- Toward Domain-Invariant Speech Recognition via Large Scale Training (2018) — 114 citations
- Monotonic Recurrent Neural Network Transducer and Decoding Strategies (2019) — 51 citations
- Domain Adaptation Using Factorized Hidden Layer for Robust Automatic Speech Recognition (2018) — 37 citations