Micah Goldblum
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 10%
- Computer Networks and Communications
- Information Systems
- Co-authors
- Tom GoldsteinAvi SchwarzschildJonas GeipingAleksander MądryXinyun ChenBo LiChulin XieDawn Song
- Topics
- Adversarial Robustness in Machine Learning (12 papers)Anomaly Detection Techniques and Applications (5 papers)Domain Adaptation and Few-Shot Learning (5 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingIEEE Transactions on Multimedia
- Partner nations
- United StatesChinaGermany
In The Last Decade
Micah Goldblum
17 papers receiving 377 citations
Hit Papers
Peers
Comparison fields: 5 of 74
- Artificial Intelligence 231
- Computer Vision and Pattern Recognition 147
- Signal Processing 70
- Computer Networks and Communications 38
- Information Systems 29
Countries citing papers authored by Micah Goldblum
This map shows the geographic impact of Micah Goldblum'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 Micah Goldblum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Micah Goldblum more than expected).
Fields of papers citing papers by Micah Goldblum
This network shows the impact of papers produced by Micah Goldblum. 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 Micah Goldblum. The network helps show where Micah Goldblum may publish in the future.
Co-authorship network of co-authors of Micah Goldblum
This figure shows the co-authorship network connecting the top 25 collaborators of Micah Goldblum. A scholar is included among the top collaborators of Micah Goldblum based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Micah Goldblum. Micah Goldblum is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 5 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 65 | |
| 9 | 62 | |
| 10 | 56 | |
| 11 | Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defensesbreakdown → | 134 |
| 12 | Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks | 1 |
| 13 | LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition | 38 |
| 14 | Protecting Proprietary Data: Poisoning for Secure Dataset Release | 1 |
| 15 | 9 | |
| 16 | Preparing for the Worst: Making Networks Less Brittle with Adversarial Batch Normalization | 2 |
| 17 | Truth or backpropaganda? An empirical investigation of deep learning theory | 2 |
| 18 | Adversarially Robust Few-Shot Learning: A Meta-Learning Approach | 2 |
| 19 | Data Augmentation for Meta-Learning | 1 |
| 20 | Robust Few-Shot Learning with Adversarially Queried Meta-Learners | 3 |
About Micah Goldblum
Micah Goldblum is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 21 papers that have together received 386 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (12 papers), Anomaly Detection Techniques and Applications (5 papers) and Domain Adaptation and Few-Shot Learning (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (147 citations), Artificial Intelligence (231 citations) and Signal Processing (70 citations). Micah Goldblum has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Tom Goldstein, Avi Schwarzschild, Jonas Geiping, Aleksander Mądry, Xinyun Chen, Bo Li, Chulin Xie, Dawn Song, Dimitris Tsipras and Gowthami Somepalli. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Transactions on Multimedia.
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.