Sri Karlapati
Artificial Intelligence · 2020–2024
A researcher in the Science corpus: 5 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 124 citations into it
- Generative Models — 40 citations into it
- Computer Vision and Pattern Recognition — 33 citations into it
Whom Sri Karlapati trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Karen Simonyan
- Alex Krizhevsky
- Alex Graves
- Ilya Sutskever
- Kaiming He
- Yann LeCun
- Aäron van den Oord
Who trusts Sri Karlapati overall
Papers from Sri Karlapati's perspective
Ordered by how strongly the researchers Sri Karlapati trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- 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
- 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)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data (2024) — 125 citations
- eCat: An End-to-End Model for Multi-Speaker TTS & Many-to-Many Fine-Grained Prosody Transfer (2023) — 3 citations
- A Comparative Analysis of Pretrained Language Models for Text-to-Speech (2023) — 3 citations
- CopyCat2: A Single Model for Multi-Speaker TTS and Many-to-Many Fine-Grained Prosody Transfer (2022) — 17 citations
- CopyCat: Many-to-Many Fine-Grained Prosody Transfer for Neural Text-to-Speech (2020) — 74 citations