Daniel J. Fremont
- Artificial Intelligence
- Software top 10%
- Automotive Engineering
- Computational Theory and Mathematics
- Computer Networks and Communications
- Co-authors
- Sanjit A. SeshiaKuldeep S. MeelMoshe Y. VardiSupratik ChakrabortyAlberto Sangiovanni‐VincentelliShromona GhoshTommaso DreossiXiangyu Yue
- Topics
- Formal Methods in Verification (5 papers)Machine Learning and Algorithms (4 papers)Bayesian Modeling and Causal Inference (3 papers)
- Journals
- Machine LearningComputers in entertainmentarXiv (Cornell University)
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Daniel J. Fremont
9 papers receiving 115 citations
Peers
Comparison fields: 5 of 26
- Artificial Intelligence 68
- Software 31
- Automotive Engineering 26
- Computational Theory and Mathematics 22
- Computer Networks and Communications 15
Countries citing papers authored by Daniel J. Fremont
This map shows the geographic impact of Daniel J. Fremont'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 J. Fremont with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel J. Fremont more than expected).
Fields of papers citing papers by Daniel J. Fremont
This network shows the impact of papers produced by Daniel J. Fremont. 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 J. Fremont. The network helps show where Daniel J. Fremont may publish in the future.
Co-authorship network of co-authors of Daniel J. Fremont
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel J. Fremont. A scholar is included among the top collaborators of Daniel J. Fremont 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 Daniel J. Fremont. Daniel J. Fremont is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 40 | |
| 3 | 0 | |
| 4 | 6 | |
| 5 | Scenic: Language-Based Scene Generation. | 7 |
| 6 | 5 | |
| 7 | 4 | |
| 8 | Constrained Sampling and Counting: Universal Hashing Meets SAT Solving | 15 |
| 9 | Speeding Up SMT-Based Quantitative Program Analysis. | 1 |
| 10 | 39 |
About Daniel J. Fremont
Daniel J. Fremont is a scholar working on Software, Computational Theory and Mathematics and Artificial Intelligence, having authored 10 papers that have together received 118 indexed citations. Recurring topics across this work include Formal Methods in Verification (5 papers), Machine Learning and Algorithms (4 papers) and Bayesian Modeling and Causal Inference (3 papers). The work is most often cited by research in Software (31 citations), Automotive Engineering (26 citations) and Artificial Intelligence (68 citations). Daniel J. Fremont has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Sanjit A. Seshia, Kuldeep S. Meel, Moshe Y. Vardi, Supratik Chakraborty, Alberto Sangiovanni‐Vincentelli, Shromona Ghosh, Tommaso Dreossi, Xiangyu Yue, Edward Kim and Dror Fried. Their work appears in journals such as Machine Learning, Computers in entertainment and arXiv (Cornell University).
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.