Guha Balakrishnan

Computer Vision and Pattern Recognition · 2013–2023

A researcher in the Science corpus: 9 papers; trusts 583 researchers and is trusted by 24 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 220 citations into it; #7,559 of 21,575 by trust here, #5,890 by citations
• Artificial Intelligence — 58 citations into it; #30,828 of 35,345 by trust here, #18,186 by citations
• Radiology, Nuclear Medicine and Imaging — 50 citations into it; #2,020 of 3,265 by trust here, #2,073 by citations
• Generative Models — 30 citations into it
• Biomedical Engineering — 26 citations into it; #1,058 of 10,734 by trust here, #3,931 by citations
• Cognitive Neuroscience — 26 citations into it
• Aerospace Engineering — 24 citations into it
• Media Technology — 21 citations into it

Whom Guha Balakrishnan trusts overall

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

1. Diederik P. Kingma
2. John Ashburner
3. Karen Simonyan
4. Geoffrey E. Hinton
5. Kaiming He
6. Alex Krizhevsky
7. Bruce Fischl
8. Andrew Zisserman
9. Yann LeCun
10. Yoshua Bengio

Who trusts Guha Balakrishnan overall

1. Adrian V. Dalca
2. Maithra Raghu
3. Grant Haskins
4. Amy Zhao
5. Daniel J. McDuff
6. Tony C. W. Mok
7. Xiaobai Li
8. Boah Kim
9. Yabo Fu
10. Junyu Chen

Papers from Guha Balakrishnan's perspective

Ordered by how strongly the researchers Guha Balakrishnan 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. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Synthesizing Images of Humans in Unseen Poses (2018) — 327 citations
• Towards causal benchmarking of bias in face analysis algorithms (2020) — 100 citations
• VoxelMorph: A Learning Framework for Deformable Medical Image Registration (2018) — 2,150 citations
• Detecting Pulse from Head Motions in Video (2013) — 585 citations
• An Unsupervised Learning Model for Deformable Medical Image Registration (2018) — 703 citations
• WIRE: Wavelet Implicit Neural Representations (2023) — 305 citations
• Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces (2019) — 487 citations
• Data Augmentation Using Learned Transformations for One-Shot Medical Image Segmentation (2019) — 448 citations
• Unsupervised Learning for Fast Probabilistic Diffeomorphic Registration (2018) — 415 citations