Jennifer Tour Chayes

Artificial Intelligence · 2003–2023

A researcher in the Science corpus: 18 papers; trusts 34 researchers and is trusted by 30 researchers here, as inferred from the citation graph.

Subfields

Artificial Intelligence — 133 citations into it; #16,570 of 35,345 by trust here, #3,467 by citations
Statistical and Nonlinear Physics — 61 citations into it; #4,674 of 10,127 by trust here, #581 by citations
Computational Theory and Mathematics — 53 citations into it; #1,608 of 12,182 by trust here, #1,047 by citations
Computer Vision and Pattern Recognition — 41 citations into it; #15,432 of 21,575 by trust here, #4,402 by citations
Optimization & Training — 36 citations into it; #2,031 of 2,601 by trust here, #560 by citations
Management Science and Operations Research — 28 citations into it
Computer Networks and Communications — 25 citations into it; #6,619 of 9,886 by trust here, #8,191 by citations
Statistics and Probability — 21 citations into it

Whom Jennifer Tour Chayes trusts overall

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

Who trusts Jennifer Tour Chayes overall

Papers from Jennifer Tour Chayes's perspective

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

Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
ImageNet classification with deep convolutional neural networks
Long Short-Term Memory
Gradient-based learning applied to document recognition
Attention is All you Need (Neural Information Processing Systems)
Learning Multiple Layers of Features from Tiny Images
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
ImageNet: A large-scale hierarchical image database
ImageNet Large Scale Visual Recognition Challenge

Their papers

Entropy-SGD: biasing gradient descent into wide valleys (2016) — 882 citations
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting (2019) — 587 citations
Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemes (2016) — 183 citations
What’s in a Name? Reducing Bias in Bios without Access to Protected Attributes (2019) — 86 citations
Convergent Sequences of Dense Graphs I: Subgraph Frequencies, Metric Properties and Testing (2007) — 699 citations
Counting Graph Homomorphisms (2006) — 213 citations
Moments of Two-Variable Functions and the Uniqueness of Graph Limits (2008) — 160 citations
Convergent Sequences of Dense Graphs II. Multiway Cuts and Statistical Physics (2012) — 355 citations
Random subgraphs of finite graphs : II. The lace expansion and the triangle condition (2004) — 107 citations
Percolation on dense graph sequences. (2007) — 93 citations
ChatGPT Chemistry Assistant for Text Mining and the Prediction of MOF Synthesis (2023) — 429 citations
Visualizing the Consequences of Climate Change Using Cycle-Consistent Adversarial Networks (2019) — 43 citations
MLSys: The New Frontier of Machine Learning Systems (2019) — 25 citations
Tackling Climate Change with Machine Learning (2019) — 1,184 citations
An $L^{p}$ theory of sparse graph convergence II: LD convergence, quotients and right convergence (2014) — 98 citations
Asymptotic behavior and distributional limits of preferential attachment graphs (2014) — 111 citations
Maximizing Social Influence in Nearly Optimal Time (2012) — 939 citations
Directed scale-free graphs (2003) — 440 citations