Vladimir I. Pavlovic
Computer Vision and Pattern Recognition · 2000–2018
A researcher in the Science corpus: 6 papers; trusts 261 researchers and is trusted by 31 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 65 citations into it; #5,354 of 21,575 by trust here, #6,954 by citations
- Artificial Intelligence — 47 citations into it; #12,304 of 35,345 by trust here, #13,544 by citations
- Representation & Self-Supervised Learning — 28 citations into it
- Cancer Research — 9 citations into it
- Probabilistic & Bayesian Methods — 8 citations into it
- Signal Processing — 7 citations into it
- Generative Models — 6 citations into it
- Multimodal Learning — 6 citations into it
Whom Vladimir I. Pavlovic trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Robert Tibshirani
- David M. Blei
- Victor Lavrenko
- Michael I. Jordan
- Geoffrey E. Hinton
- Jia Li
- Diederik P. Kingma
- Yann LeCun
- Raghavan Manmatha
- Alex Krizhevsky
Who trusts Vladimir I. Pavlovic overall
- Emily B. Fox
- Antoni B. Chan
- Graham W. Taylor
- Feng Zhou
- Dario Pavllo
- Tony Jebara
- C. V. Jawahar
- Emad Barsoum
- Katerina Fragkiadaki
- Yunchao Gong
Papers from Vladimir I. Pavlovic's perspective
Ordered by how strongly the researchers Vladimir I. Pavlovic trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- 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)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- A New Baseline for Image Annotation (2008) — 511 citations
- Face tracking and recognition with visual constraints in real-world videos (2008) — 517 citations
- Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach (2018) — 193 citations
- Baselines for Image Annotation (2010) — 217 citations
- Central Subspace Dimensionality Reduction Using Covariance Operators (2011) — 24 citations
- Learning Switching Linear Models of Human Motion (2000) — 436 citations