Stefanie Jegelka
-
- Advanced Image and Video Retrieval Techniques 7
- Artificial Intelligence top 2%
- Machine Learning and Algorithms 13
- Domain Adaptation and Few-Shot Learning 8
- Advanced Graph Neural Networks 7
- Bayesian Methods and Mixture Models 5
-
- Complexity and Algorithms in Graphs 12
-
- Sparse and Compressive Sensing Techniques 6
-
- Markov Chains and Monte Carlo Methods 6
- Co-authors
- Jeff BilmesHyun Oh SongElsa OlivettiEdward KimKevin HuangVivek RathodKevin MurphyKeyulu Xu
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceComputational Theory and Mathematics
- Journals
- npj Computational Materials (1 paper)Nature Communications (1 paper)Nature Reviews Methods Primers (1 paper)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Stefanie Jegelka
68 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Computer Vision and Pattern Recognition 488
- Artificial Intelligence 657
- Computational Theory and Mathematics 265
- Statistical and Nonlinear Physics 82
- Computer Graphics and Computer-Aided Design 21
Countries citing papers authored by Stefanie Jegelka
This map shows the geographic impact of Stefanie Jegelka's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Stefanie Jegelka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefanie Jegelka more than expected).
Fields of papers citing papers by Stefanie Jegelka
This network shows the impact of papers produced by Stefanie Jegelka. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Stefanie Jegelka. The network helps show where Stefanie Jegelka may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Stefanie Jegelka, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 4 | |
| 2 | How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks | 2021 | 6 |
| 3 | What Can Neural Networks Reason About | 2020 | 11 |
| 4 | Estimating Generalization under Distribution Shifts via Domain-Invariant Representations | 2020 | 1 |
| 5 | Minimizing approximately submodular functions. | 2019 | 2 |
| 6 | Flexible Modeling of Diversity with Strongly Log-Concave Distributions | 2019 | 1 |
| 7 | Representation Learning on Graphs with Jumping Knowledge Networks | 2018 | 131 |
| 8 | ResNet with one-neuron hidden layers is a Universal Approximator | 2018 | 25 |
| 9 | Batched Large-scale Bayesian Optimization in High-dimensional Spaces | 2017 | 9 |
| 10 | Column Subset Selection via Polynomial Time Dual Volume Sampling | 2017 | 1 |
| 11 | 2017 | 175 | |
| 12 | Learnable Structured Clustering Framework for Deep Metric Learning. | 2016 | 6 |
| 13 | Gaussian quadrature for matrix inverse forms with applications | 2016 | 3 |
| 14 | Efficient Sampling for k-Determinantal Point Processes | 2016 | 5 |
| 15 | One-Bit Object Detection: On learning to localize objects with minimal supervision. | 2014 | 4 |
| 16 | Parallel Double Greedy Submodular Maximization | 2014 | 11 |
| 17 | Online Submodular Minimization for Combinatorial Structures | 2011 | 8 |
| 18 | Approximation Bounds for Inference using Cooperative Cuts | 2011 | 9 |
| 19 | Notes on Graph Cuts with Submodular Edge Weights | 2009 | 1 |
| 20 | Fast kernel ICA using an approximate Newton method | 2007 | 7 |
About Stefanie Jegelka
Stefanie Jegelka is a scholar working on Computational Mathematics, Artificial Intelligence, Computer Graphics and Computer-Aided Design, Computational Theory and Mathematics and Statistics and Probability, having authored 73 papers that have together received 1.4k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (13 papers), Complexity and Algorithms in Graphs (12 papers), Domain Adaptation and Few-Shot Learning (8 papers), Advanced Graph Neural Networks (7 papers), Advanced Image and Video Retrieval Techniques (7 papers), Sparse and Compressive Sensing Techniques (6 papers), Markov Chains and Monte Carlo Methods (6 papers) and Bayesian Methods and Mixture Models (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (488 citations), Artificial Intelligence (657 citations), Computational Theory and Mathematics (265 citations), Statistical and Nonlinear Physics (82 citations) and Computer Graphics and Computer-Aided Design (21 citations). Stefanie Jegelka has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Jeff Bilmes, Hyun Oh Song, Elsa Olivetti, Edward Kim, Kevin Huang, Vivek Rathod, Kevin Murphy, Keyulu Xu, Ken‐ichi Kawarabayashi and Chengtao Li. Their work appears in journals such as npj Computational Materials, Nature Communications, Nature Reviews Methods Primers, Bioinformatics and International Journal of Computer Vision.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.