Varun Chandrasekaran
Artificial Intelligence · 2019–2023
A researcher in the Science corpus: 4 papers; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 88 citations into it
- Safety, Robustness & Interpretability — 46 citations into it
- Computer Vision and Pattern Recognition — 20 citations into it
- Optimization & Training — 16 citations into it
- Computer Networks and Communications — 14 citations into it
- Information Systems — 8 citations into it
- Representation & Self-Supervised Learning — 7 citations into it
- Statistical Learning Theory — 6 citations into it
Whom Varun Chandrasekaran trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Kaiming He
- Vladimir Naumovich Vapnik
- Yann LeCun
- Ilya Sutskever
- Karen Simonyan
- Blaine Nelson
Who trusts Varun Chandrasekaran overall
Papers from Varun Chandrasekaran's perspective
Ordered by how strongly the researchers Varun Chandrasekaran trusts endorse each paper. Same corpus, a different order for every researcher.
- 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Sparks of Artificial General Intelligence: Early experiments with GPT-4 (2023) — 4,318 citations
- Machine Unlearning (2019) — 1,538 citations
- On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping (2020) — 157 citations
- Unrolling SGD: Understanding Factors Influencing Machine Unlearning (2021) — 342 citations