Hedvig Kjellström

Artificial Intelligence · 2000–2019

A researcher in the Science corpus: 9 papers; trusts 537 researchers and is trusted by 774 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 177 citations into it; #20,312 of 35,345 by trust here, #16,471 by citations
• Computer Vision and Pattern Recognition — 113 citations into it; #1,561 of 21,575 by trust here, #4,344 by citations
• Probabilistic & Bayesian Methods — 103 citations into it
• Optimization & Training — 51 citations into it
• Statistics and Probability — 39 citations into it
• Generative Models — 31 citations into it
• Management Science and Operations Research — 26 citations into it
• Model Architectures — 18 citations into it

Whom Hedvig Kjellström trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Radford M. Neal
5. David M. Blei
6. Michael I. Jordan
7. Yoshua Bengio
8. Yann LeCun
9. Karen Simonyan
10. L. Eon Bottou

Who trusts Hedvig Kjellström overall

1. Leonid Sigal
2. Ronald Poppe
3. Cristian Sminchisescu
4. Deva Ramanan
5. Michael J. Black
6. David J. Fleet
7. Bugra Tekin
8. Saad M. Khan
9. Liang Wang
10. Bill Triggs

Papers from Hedvig Kjellström's perspective

Ordered by how strongly the researchers Hedvig Kjellström trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Stochastic Tracking of 3D Human Figures Using 2D Image Motion (2000) — 866 citations
• Implicit Probabilistic Models of Human Motion for Synthesis and Tracking (2002) — 398 citations
• Hands in action: real-time 3D reconstruction of hands in interaction with objects (2010) — 143 citations
• Deep Representation Learning for Human Motion Prediction and Classification (2017) — 443 citations
• Balanced Mini-batch Sampling for SGD Using Determinantal Point Processes (2017) — 34 citations
• Advances in Variational Inference (2017) — 815 citations
• Non-Parametric Calibration for Classification (2019) — 95 citations
• Stochastic Learning on Imbalanced Data: Determinantal Point Processes for Mini-batch Diversification (2017) — 58 citations
• Audio-visual classification and detection of human manipulation actions (2014) — 58 citations