Rakesh Balachandar
Artificial Intelligence · 2017
A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 8 citations into it
- Computer Vision and Pattern Recognition — 8 citations into it
- Optimization & Training — 5 citations into it
Whom Rakesh Balachandar trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Rakesh Balachandar overall
Papers from Rakesh Balachandar's perspective
Ordered by how strongly the researchers Rakesh Balachandar 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
- Practical Recommendations for Gradient-Based Training of Deep Architectures
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet Large Scale Visual Recognition Challenge