Daniel M. Roy
Impact in
- Software top 5%
- Software Testing and Debugging Techniques
- Artificial Intelligence top 2%
- Security and Verification in Computing
- Logic, programming, and type systems
- Bayesian Modeling and Causal Inference
- Bayesian Methods and Mixture Models
Papers in
-
- Bayesian Methods and Mixture Models 7
- Stochastic Gradient Optimization Techniques 6
- Bayesian Modeling and Causal Inference 6
- Machine Learning and Algorithms 4
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- Probability and Statistical Research 4
- Statistical Methods and Inference 4
- Co-authors
- Martin Rinard (5 shared papers)Cristian Cadar (3 shared papers)Peter Orbanz (1 shared paper)William S. Beebee (1 shared paper)Yee Whye Teh (2 shared papers)David A. Sontag (1 shared paper)Saša Misailovíc (2 shared papers)Josh Tenenbaum (6 shared papers)
- Journals
- The Annals of Statistics (4 papers)Bernoulli (2 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Journal of Machine Learning Research (1 paper)Bayesian Analysis (1 paper)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Daniel M. Roy
43 papers receiving 871 citations
Peers
Comparison fields: 5 of 66
- Software 113
- Artificial Intelligence 472
- Statistical and Nonlinear Physics 105
- Hardware and Architecture 56
- Computer Networks and Communications 138
Countries citing papers authored by Daniel M. Roy
This map shows the geographic impact of Daniel M. Roy'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 M. Roy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel M. Roy more than expected).
Fields of papers citing papers by Daniel M. Roy
This network shows the impact of papers produced by Daniel M. Roy. 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 M. Roy. The network helps show where Daniel M. Roy may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel M. Roy, 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 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Enhancing server availability and security through failure-oblivious computing | 2004 | 256 |
| 2 | 2014 | 109 | |
| 3 | 2005 | 71 | |
| 4 | 2011 | 65 | |
| 5 | Complexity of Inference in Latent Dirichlet Allocation | 2011 | 51 |
| 6 | The Mondrian Process | 2008 | 50 |
| 7 | 2007 | 38 | |
| 8 | 2011 | 38 | |
| 9 | The Lottery Ticket Hypothesis at Scale | 2019 | 29 |
| 10 | Efficient Bayesian task-level transfer learning | 2007 | 27 |
| 11 | 2019 | 22 | |
| 12 | Bayesian Policy Search with Policy Priors | 2011 | 19 |
| 13 | 2011 | 18 | |
| 14 | 2016 | 13 | |
| 15 | 2009 | 11 | |
| 16 | 2019 | 9 | |
| 17 | 2018 | 8 | |
| 18 | 2019 | 8 | |
| 19 | 2021 | 8 | |
| 20 | Exact and approximate sampling by systematic stochastic search | 2009 | 6 |
About Daniel M. Roy
Daniel M. Roy is a scholar working on Artificial Intelligence, Statistics and Probability, Computational Theory and Mathematics, Statistical and Nonlinear Physics and Management Science and Operations Research, having authored 45 papers that have together received 916 indexed citations. Recurring topics across this work include Computability, Logic, AI Algorithms (8 papers), Bayesian Methods and Mixture Models (7 papers), Stochastic Gradient Optimization Techniques (6 papers), Bayesian Modeling and Causal Inference (6 papers), Probability and Statistical Research (4 papers), Machine Learning and Algorithms (4 papers), Statistical Methods and Inference (4 papers) and Advanced Bandit Algorithms Research (3 papers). The work is most often cited by research in Software (113 citations), Artificial Intelligence (472 citations), Statistical and Nonlinear Physics (105 citations), Hardware and Architecture (56 citations) and Computer Networks and Communications (138 citations). Daniel M. Roy has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Martin Rinard, Cristian Cadar, Peter Orbanz, William S. Beebee, Yee Whye Teh, David A. Sontag, Saša Misailovíc, Josh Tenenbaum, Leslie Pack Kaelbling and Victor Veitch. Their work appears in journals such as The Annals of Statistics, Bernoulli, IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Machine Learning Research and Bayesian Analysis.
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.