Harkirat Singh Behl
Artificial Intelligence · 2019–2024
A researcher in the Science corpus: 5 papers; trusts 126 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 151 citations into it; #25,194 of 35,345 by trust here, #8,210 by citations
- Computer Vision and Pattern Recognition — 129 citations into it
- Representation & Self-Supervised Learning — 14 citations into it
- Optimization & Training — 7 citations into it
- Reinforcement Learning — 6 citations into it
Whom Harkirat Singh Behl trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Hugo Larochelle
- Ruslan Salakhutdinov
- Oriol Vinyals
- J. Urgen Schmidhuber
- Alex Krizhevsky
- Diederik P. Kingma
- Yann LeCun
- Chelsea Finn
Who trusts Harkirat Singh Behl overall
Papers from Harkirat Singh Behl's perspective
Ordered by how strongly the researchers Harkirat Singh Behl 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Generalized Decoding for Pixel, Image, and Language (2022) — 380 citations
- Textbooks Are All You Need (2023) — 626 citations
- Phi-4 Technical Report (2024) — 716 citations
- Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone (2024) — 2,340 citations
- Alpha MAML: Adaptive Model-Agnostic Meta-Learning (2019) — 72 citations