Anna Choromanska

2.6k citations
30 papers · 798 · h-index 12

Impact in

    • Adversarial Robustness in Machine Learning
    • Stochastic Gradient Optimization Techniques
    • Neural Networks and Applications
    • Domain Adaptation and Few-Shot Learning
    • Anomaly Detection Techniques and Applications
    • Advanced Neural Network Applications

Papers in

    • Stochastic Gradient Optimization Techniques 6
    • Machine Learning and Data Classification 5
    • Adversarial Robustness in Machine Learning 4
    • Machine Learning and Algorithms 4
    • Anomaly Detection Techniques and Applications 3
    • Explainable Artificial Intelligence (XAI) 2
    • Advanced Neural Network Applications 8

Anna Choromanska

27 papers receiving 774 citations

Peers

Anna Choromanska
Comparison fields: 5 of 99
  • Artificial Intelligence 502
  • Computer Vision and Pattern Recognition 292
  • Biophysics 30
  • Automotive Engineering 62
  • Health Informatics 6
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Citations per year

Countries citing papers authored by Anna Choromanska

Since Specialization
Citations

This map shows the geographic impact of Anna Choromanska'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 Anna Choromanska with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anna Choromanska more than expected).

Fields of papers citing papers by Anna Choromanska

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anna Choromanska. 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 Anna Choromanska. The network helps show where Anna Choromanska may publish in the future.

Co-authors

The 25 scholars most cited alongside Anna Choromanska, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Anna Choromanska Line = papers co-authored together Anna Choromanska links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014288
2 2019153
3 201859
4 201738
5
VisualBackProp: visualizing CNNs for autonomous driving.
201636
6
The Loss Surface of Multilayer Networks.
201430
7 201229
8 201926
9
Open Problem: The landscape of the loss surfaces of multilayer networks
201525
10 201820
11 201415
12 201911
13 202010
14
Skin Lesion Segmentation and Classification with Deep Learning System.
201910
15 20229
16
Majorization for CRFs and Latent Likelihoods
20127
17 20157
18 20166
19
Beyond Backprop: Alternating Minimization with co-Activation Memory.
20184
20
Online clustering with experts
20113

About Anna Choromanska

Anna Choromanska is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Aerospace Engineering, Statistical and Nonlinear Physics and Biophysics, having authored 30 papers that have together received 798 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (8 papers), Stochastic Gradient Optimization Techniques (6 papers), Machine Learning and Data Classification (5 papers), Adversarial Robustness in Machine Learning (4 papers), Machine Learning and Algorithms (4 papers), Anomaly Detection Techniques and Applications (3 papers), Cell Image Analysis Techniques (3 papers) and Explainable Artificial Intelligence (XAI) (2 papers). The work is most often cited by research in Artificial Intelligence (502 citations), Computer Vision and Pattern Recognition (292 citations), Biophysics (30 citations), Automotive Engineering (62 citations) and Health Informatics (6 citations). Anna Choromanska has collaborated with scholars based in United States, Switzerland and Poland. Frequent co-authors include Yann LeCun, Gérard Ben Arous, Mikael Henaff, Michaël Mathieu, P. Krishnamurthy, Farshad Khorrami, Riccardo Zecchina, Levent Sagun, Pratik Chaudhari and Stefano Soatto. Their work appears in journals such as Robotics and Autonomous Systems, IEEE Transactions on Intelligent Vehicles, IEEE Robotics and Automation Letters, Frontiers in Neural Circuits and Theoretical Computer Science.

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.

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