A. Ihler
Artificial Intelligence · 2003–2018
A researcher in the Science corpus: 12 papers; trusts 70 researchers and is trusted by 20 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 37 citations into it; #8,989 of 35,345 by trust here, #8,077 by citations
- Probabilistic & Bayesian Methods — 30 citations into it
- Computer Networks and Communications — 23 citations into it; #6,158 of 9,886 by trust here, #3,993 by citations
- Computer Vision and Pattern Recognition — 23 citations into it
- Evaluation & Benchmarks — 12 citations into it
- Computational Mechanics — 10 citations into it
- Statistics and Probability — 10 citations into it; #10,140 of 12,932 by trust here, #10,275 by citations
- Electrical and Electronic Engineering — 9 citations into it; #15,595 of 16,539 by trust here, #10,998 by citations
Whom A. Ihler trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Arnaud Doucet
- William T. Freeman
- Bernard Walter Silverman
- Stuart Geman
- Geoffrey E. Hinton
- Martin J. Wainwright
- Erik B. Sudderth
- Pierre Del Moral
- Daniel Scharstein
- Yair Weiss
Who trusts A. Ihler overall
- Le Song
- Arthur Gretton
- Ali O. Ulusoy
- Danny Bickson
- Bo Dai
- Kenji Fukumizu
- Martin J. Wainwright
- Krikamol Muandet
- Michael J. Black
- Shenlong Wang
Papers from A. Ihler's perspective
Ordered by how strongly the researchers A. Ihler 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)
- 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)
- 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
- Nonparametric belief propagation (2003) — 615 citations
- Fast collapsed gibbs sampling for latent dirichlet allocation (2008) — 627 citations
- Distributed Estimation, Information Loss and Exponential Families (2014) — 61 citations
- Nonparametric belief propagation for self-localization of sensor networks (2005) — 567 citations
- ContextNet: Deep learning for Star Galaxy Classification (2018) — 7 citations
- Variational Inference for Crowdsourcing (2012) — 375 citations
- Feed-forward Hierarchical Model of the Ventral Visual Stream Applied to Functional Brain Image Classification (2012) — 373 citations
- Distributed Parameter Estimation via Pseudo-likelihood (2012) — 36 citations
- Particle Belief Propagation (2009) — 155 citations
- Fault Identification Via Nonparametric Belief Propagation (2009) — 21 citations
- Loopy Belief Propagation: Convergence and Effects of Message Errors (2005) — 370 citations
- Efficient Multiscale Sampling from Products of Gaussian Mixtures (2003) — 106 citations