Daniel Lowd
Impact in
- Artificial Intelligence top 0.5%
- Adversarial Robustness in Machine Learning
- Topic Modeling
- Bayesian Modeling and Causal Inference
- Anomaly Detection Techniques and Applications
- Natural Language Processing Techniques
- Signal Processing top 1%
- Advanced Malware Detection Techniques
Papers in
-
- Bayesian Modeling and Causal Inference 20
- Machine Learning and Algorithms 11
- Topic Modeling 11
- Semantic Web and Ontologies 9
- Adversarial Robustness in Machine Learning 9
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- Data Mining Algorithms and Applications 5
- Co-authors
- Pedro Domingos (17 shared papers)Christopher Meek (2 shared papers)Javid Ebrahimi (4 shared papers)Dejing Dou (6 shared papers)Anyi Rao (1 shared paper)Jesse J. Davis (3 shared papers)Dejing Dou (3 shared papers)Hoifung Poon (6 shared papers)
- Journals
- Synthesis lectures on artificial intelligence and machine learning (5 papers)Communications of the ACM (1 paper)Machine Learning (1 paper)Journal of Machine Learning Research (1 paper)Lecture notes in computer science (8 papers)
- Partner nations
- United StatesGermanyBelgium
In The Last Decade
Daniel Lowd
53 papers receiving 2.5k citations
Daniel Lowd's Hit Papers
Peers
Comparison fields: 5 of 124
- Artificial Intelligence 2.2k
- Signal Processing 657
- Information Systems 508
- Computer Networks and Communications 421
- Management Science and Operations Research 177
Countries citing papers authored by Daniel Lowd
This map shows the geographic impact of Daniel Lowd'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 Daniel Lowd with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Lowd more than expected).
Fields of papers citing papers by Daniel Lowd
This network shows the impact of papers produced by Daniel Lowd. 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 Daniel Lowd. The network helps show where Daniel Lowd may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Lowd, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | HotFlip: White-Box Adversarial Examples for Text Classification Hit paper breakdown → | 2018 | 612 |
| 2 | Adversarial learning Hit paper breakdown → | 2005 | 501 |
| 3 | 2009 | 258 | |
| 4 | 2005 | 234 | |
| 5 | Good Word Attacks on Statistical Spam Filters. | 2005 | 172 |
| 6 | 2007 | 138 | |
| 7 | 2009 | 88 | |
| 8 | Markov logic | 2008 | 58 |
| 9 | Learning Sum-Product Networks with Direct and Indirect Variable Interactions | 2014 | 58 |
| 10 | 2010 | 47 | |
| 11 | 2012 | 42 | |
| 12 | 2016 | 40 | |
| 13 | Learning Markov Networks With Arithmetic Circuits | 2013 | 34 |
| 14 | 2008 | 32 | |
| 15 | 2017 | 30 | |
| 16 | 2014 | 28 | |
| 17 | A Joint Sentiment-Target-Stance Model for Stance Classification in Tweets | 2016 | 27 |
| 18 | 2008 | 25 | |
| 19 | 2024 | 25 | |
| 20 | Improving Markov network structure learning using decision trees | 2014 | 22 |
About Daniel Lowd
Daniel Lowd is a scholar working on Artificial Intelligence, Information Systems, Signal Processing, Computer Networks and Communications and Management Science and Operations Research, having authored 55 papers that have together received 2.7k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (20 papers), Machine Learning and Algorithms (11 papers), Topic Modeling (11 papers), Semantic Web and Ontologies (9 papers), Adversarial Robustness in Machine Learning (9 papers), Data Mining Algorithms and Applications (5 papers), Biomedical Text Mining and Ontologies (4 papers) and Data Quality and Management (4 papers). The work is most often cited by research in Artificial Intelligence (2.2k citations), Signal Processing (657 citations), Information Systems (508 citations), Computer Networks and Communications (421 citations) and Management Science and Operations Research (177 citations). Daniel Lowd has collaborated with scholars based in United States, Germany and Belgium. Frequent co-authors include Pedro Domingos, Christopher Meek, Javid Ebrahimi, Dejing Dou, Anyi Rao, Jesse J. Davis, Dejing Dou, Hoifung Poon, Parag Singla and Stanley Kok. Their work appears in journals such as Synthesis lectures on artificial intelligence and machine learning, Communications of the ACM, Machine Learning, Journal of Machine Learning Research and Lecture notes in 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.