AkshatKumar Nigam
Artificial Intelligence · 2019–2022
A researcher in the Science corpus: 3 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 43 citations into it
- Generative Models — 18 citations into it
- Computational Chemistry & Drug Discovery — 13 citations into it
Whom AkshatKumar Nigam trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from AkshatKumar Nigam's perspective
Ordered by how strongly the researchers AkshatKumar Nigam trusts endorse each paper. Same corpus, a different order for every researcher.
- Auto-Encoding Variational Bayes (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- WaveNet: A Generative Model for Raw Audio
- Learning Multiple Layers of Features from Tiny Images
Their papers
- On scientific understanding with artificial intelligence (2022) — 320 citations
- Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation (2019) — 957 citations
- Data-Driven Strategies for Accelerated Materials Design (2021) — 369 citations