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ORCIDDan Brown 0001
Person information
- affiliation: University of Waterloo, David R. Cheriton School of Computer Science, ON, Canada
- affiliation (PhD 2000): Cornell University, Ithaca, NY, USA
Other persons with the same name
- Dan Brown — disambiguation page
- Daniel G. Brown 0002
![[0000-0001-6023-5950]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-6023-5950")
— University of Washington, School of Environmental and Forest Sciences, Seattle, WA, USA (and 3 more) - Daniel G. Brown 0003 — Alcatel-Lucent Technologies, Inc., Holmdel, NJ, USA
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2020 – today
- 2024
[i11]Aisha Khatun, Daniel G. Brown:
A Study on Large Language Models' Limitations in Multiple-Choice Question Answering. CoRR abs/2401.07955 (2024)- [i10]Max Peeperkorn, Tom Kouwenhoven, Dan Brown, Anna Jordanous:
Is Temperature the Creativity Parameter of Large Language Models? CoRR abs/2405.00492 (2024) - [i9]Aisha Khatun, Daniel G. Brown:
TruthEval: A Dataset to Evaluate LLM Truthfulness and Reliability. CoRR abs/2406.01855 (2024) - [i8]Christopher Liscio, Daniel G. Brown:
Watching Popular Musicians Learn by Ear: A Hypothesis-Generating Study of Human-Recording Interactions in YouTube Videos. CoRR abs/2406.04058 (2024) - [i7]Aisha Khatun, Daniel G. Brown:
Assessing Language Models' Worldview for Fiction Generation. CoRR abs/2408.07904 (2024) - [i6]C. E. Lamb, Dan Brown, Maura R. Grossman:
Precarity and Solidarity: Preliminary results on a study of queer and disabled fiction writers' experiences with generative AI. CoRR abs/2412.04575 (2024) - 2023
- [c47]Piotr Sawicki, Marek Grzes, Fabrício Góes, Anna Jordanous, Dan Brown, Simona Paraskevopoulou, Max Peeperkorn, Aisha Khatun:
On the power of special-purpose GPT models to create and evaluate new poetry in old styles. ICCC 2023: 10-19 - [c46]Brad Spendlove, Dan Brown:
What Makes Gameplay Creative? ICCC 2023: 98-101 - [c45]Dan Brown, Max Peeperkorn:
Reviewing, Creativity, and Algorithmic Information Theory. ICCC 2023: 133-142 - [c44]Max Peeperkorn, Dan Brown, Anna Jordanous:
On Characterizations of Large Language Models and Creativity Evaluation. ICCC 2023: 143-147 - [c43]Carolyn Lamb, Dan Brown:
Should we have seen the coming storm? Transformers, society, and CC. ICCC 2023: 157-161 - [c42]Piotr Sawicki, Marek Grzes, Fabrício Góes, Dan Brown, Max Peeperkorn, Aisha Khatun:
Bits of Grass: Does GPT already know how to write like Whitman? ICCC 2023: 317-321 - [c41]Fabrício Góes, Piotr Sawicki, Marek Grzes, Marco Volpe, Dan Brown:
Is GPT-4 Good Enough to Evaluate Jokes? ICCC 2023: 367-371 - [e2]Alison Pease, João Miguel Cunha, Maya Ackerman, Daniel G. Brown:
Proceedings of the 14th International Conference on Computational Creativity, Ontario, Canada, June 19-23, 2023. Association for Computational Creativity (ACC) 2023, ISBN 978-989-54160-5-9 [contents] - [i5]Piotr Sawicki, Marek Grzes, Fabrício Góes, Dan Brown, Max Peeperkorn, Aisha Khatun:
Bits of Grass: Does GPT already know how to write like Whitman? CoRR abs/2305.11064 (2023) - [i4]Aisha Khatun, Daniel G. Brown:
Reliability Check: An Analysis of GPT-3's Response to Sensitive Topics and Prompt Wording. CoRR abs/2306.06199 (2023) - 2022
- [c40]Piotr Sawicki, Marek Grzes, Anna Jordanous, Dan Brown, Max Peeperkorn:
Training GPT-2 to represent two Romantic-era authors: challenges, evaluations and pitfalls. ICCC 2022: 34-43 - [c39]Daniel G. Brown, Dan Ventura:
Ethics, Aesthetics and Computational Creativity. ICCC 2022: 150-158 - [c38]Daniel G. Brown, Anna Jordanous:
Is style reproduction a computational creativity task? ICCC 2022: 220-229 - [i3]Fabrício Góes, Zisen Zhou, Piotr Sawicki, Marek Grzes, Daniel G. Brown:
Crowd Score: A Method for the Evaluation of Jokes using Large Language Model AI Voters as Judges. CoRR abs/2212.11214 (2022) - 2021
- [j23]Daniel G. Brown, Tiasa Mondol:
On the Problem of Small Objects. Entropy 23(11): 1524 (2021) - [j22]Tiasa Mondol, Daniel G. Brown:
Computational Creativity and Aesthetics with Algorithmic Information Theory. Entropy 23(12): 1654 (2021) - [c37]Dan Brown, Lauren Byl, Maura R. Grossman:
Are Machine Learning Corpora "Fair Dealing" under Canadian Law? ICCC 2021: 158-162 - [c36]Tiasa Mondol, Daniel G. Brown:
Incorporating Algorithmic Information Theory into Fundamental Concepts of Computational Creativity. ICCC 2021: 173-181
2010 – 2019
- 2019
- [c35]Carolyn Lamb, Daniel G. Brown:
TwitSong 3.0: Towards Semantic Revisions in Computational Poetry. ICCC 2019: 212-219 - 2018
- [j21]Carolyn Lamb, Daniel G. Brown, Charles L. A. Clarke:
Evaluating Computational Creativity: An Interdisciplinary Tutorial. ACM Comput. Surv. 51(2): 28:1-28:34 (2018) - 2017
- [c34]Carolyn Lamb, Daniel G. Brown, Charles L. A. Clarke:
Incorporating novelty, meaning, reaction and craft into computational poetry: a negative experimental result. ICCC 2017: 183-188 - 2016
- [c33]Carolyn Lamb, Daniel G. Brown, Charles L. A. Clarke:
Evaluating digital poetry: Insights from the CAT. ICCC 2016: 60-67 - 2015
- [j20]Eric Marinier, Daniel G. Brown, Brendan J. McConkey:
Pollux: platform independent error correction of single and mixed genomes. BMC Bioinform. 16: 10:1-10:12 (2015) - [c32]Carolyn Lamb, Daniel G. Brown, Charles L. A. Clarke:
Human Competence in Creativity Evaluation. ICCC 2015: 102-109 - 2014
- [j19]Margareta Ackerman, Daniel G. Brown, David Loker:
Effects of rooting via out-groups on in-group topology in phylogeny. Int. J. Bioinform. Res. Appl. 10(4/5): 426-446 (2014) - [c31]Abhishek Singhi, Daniel G. Brown:
On Cultural, Textual and Experiential Aspects of Music Mood. ISMIR 2014: 3-8 - [c30]Abhishek Singhi, Daniel G. Brown:
Are Poetry and Lyrics All That Different? ISMIR 2014: 471-476 - [e1]Dan Brown, Burkhard Morgenstern:
Algorithms in Bioinformatics - 14th International Workshop, WABI 2014, Wroclaw, Poland, September 8-10, 2014. Proceedings. Lecture Notes in Computer Science 8701, Springer 2014, ISBN 978-3-662-44752-9 [contents] - 2013
- [j18]Daniel Dexter, Daniel G. Brown:
Fast half-sibling population reconstruction: theory and algorithms. Algorithms Mol. Biol. 8: 20 (2013) - [j17]Daniel G. Brown, Jakub Truszkowski:
Fast error-tolerant quartet phylogeny algorithms. Theor. Comput. Sci. 483: 104-114 (2013) - [c29]Daniel G. Brown, Jakub Truszkowski:
LSHPlace: Fast Phylogenetic Placement Using Locality-Sensitive Hashing. Pacific Symposium on Biocomputing 2013: 310-319 - 2012
- [j16]Jakub Truszkowski, Yanqi Hao, Daniel G. Brown:
Towards a practical O(n log n) phylogeny algorithm. Algorithms Mol. Biol. 7: 32 (2012) - [j15]Andre P. Masella, Andrea K. Bartram, Jakub Truszkowski, Daniel Gregory Brown, Josh D. Neufeld:
PANDAseq: paired-end assembler for illumina sequences. BMC Bioinform. 13: 31 (2012) - [c28]Margareta Ackerman, Dan Brown, David Loker:
Effects of rooting via outgroups on ingroup topology in phylogeny. ICCABS 2012: 1-7 - [c27]Benjamin Martin, Daniel G. Brown, Pierre Hanna, Pascal Ferraro:
BLAST for Audio Sequences Alignment: A Fast Scalable Cover Identification Tool. ISMIR 2012: 529-534 - [c26]Daniel Gregory Brown, Jakub Truszkowski:
Fast Phylogenetic Tree Reconstruction Using Locality-Sensitive Hashing. WABI 2012: 14-29 - [c25]Daniel Gregory Brown, Daniel Dexter:
SibJoin: A Fast Heuristic for Half-Sibling Reconstruction. WABI 2012: 44-56 - 2011
- [j14]Jakub Truszkowski, Daniel Gregory Brown:
More accurate recombination prediction in HIV-1 using a robust decoding algorithm for HMMs. BMC Bioinform. 12: 168 (2011) - [j13]Alexander K. Hudek, Daniel Gregory Brown:
FEAST: Sensitive Local Alignment with Multiple Rates of Evolution. IEEE ACM Trans. Comput. Biol. Bioinform. 8(3): 698-709 (2011) - [c24]Daniel Gregory Brown, Jakub Truszkowski:
Fast Error-Tolerant Quartet Phylogeny Algorithms. CPM 2011: 147-161 - [c23]Daniel G. Brown:
Invited: Fast and theoretically strong algorithms for kinship discovery. ICCABS 2011: 5 - [c22]Daniel G. Brown, Jakub Truszkowski:
Towards a Practical O(n logn) Phylogeny Algorithm. WABI 2011: 14-25 - [i2]Daniel G. Brown, Jakub Truszkowski:
Fast reconstruction of phylogenetic trees using locally-sensitive hashing. CoRR abs/1111.0379 (2011) - 2010
- [j12]Daniel G. Brown, Daniil Golod:
Decoding HMMs using the k best paths: algorithms and applications. BMC Bioinform. 11(S-1): 28 (2010) - [j11]Daniel G. Brown, Jakub Truszkowski:
New decoding algorithms for Hidden Markov Models using distance measures on labellings. BMC Bioinform. 11(S-1): 40 (2010) - [c21]Hussein Hirjee, Daniel G. Brown:
Solving Misheard Lyric Search Queries Using a Probabilistic Model of Speech Sounds. ISMIR 2010: 147-152 - [c20]Daniel G. Brown, Tanya Y. Berger-Wolf:
Discovering Kinship through Small Subsets. WABI 2010: 111-123 - [i1]Daniel Gregory Brown, Jakub Truszkowski:
Fast error-tolerant quartet phylogeny algorithms. CoRR abs/1010.1866 (2010)
2000 – 2009
- 2009
- [j10]Daniil Golod, Daniel G. Brown:
A Tutorial of Techniques for Improving Standard Hidden Markov Model Algorithms. J. Bioinform. Comput. Biol. 7(4): 737-754 (2009) - [c19]Christina Boucher, Daniel G. Brown:
Detecting Motifs in a Large Data Set: Applying Probabilistic Insights to Motif Finding. BICoB 2009: 139-150 - [c18]Hussein Hirjee, Daniel G. Brown:
Automatic Detection of Internal and Imperfect Rhymes in Rap Lyrics. ISMIR 2009: 711-716 - 2008
- [c17]Christina Boucher, Daniel G. Brown, Stephane Durocher:
On the Structure of Small Motif Recognition Instances. SPIRE 2008: 269-281 - 2007
- [j9]Brona Brejová, Daniel G. Brown, Tomás Vinar:
The most probable annotation problem in HMMs and its application to bioinformatics. J. Comput. Syst. Sci. 73(7): 1060-1077 (2007) - [c16]Dan Gusfield, Yelena Frid, Daniel G. Brown:
Integer Programming Formulations and Computations Solving Phylogenetic and Population Genetic Problems with Missing or Genotypic Data. COCOON 2007: 51-64 - [c15]Christina Boucher, Daniel G. Brown, Paul Church:
A Graph Clustering Approach to Weak Motif Recognition. WABI 2007: 149-160 - 2006
- [j8]Emily W. Xu, Paul Kearney, Daniel G. Brown:
The Use of Functional Domains to Improve Transmembrane Protein Topology Prediction. J. Bioinform. Comput. Biol. 4(1): 109-124 (2006) - [j7]Jinbo Xu, Daniel G. Brown, Ming Li, Bin Ma:
Optimizing Multiple Spaced Seeds for Homology Search. J. Comput. Biol. 13(7): 1355-1368 (2006) - [j6]Daniel G. Brown, Ian M. Harrower:
Integer Programming Approaches to Haplotype Inference by Pure Parsimony. IEEE ACM Trans. Comput. Biol. Bioinform. 3(2): 141-154 (2006) - [c14]Brona Brejová, Daniel G. Brown, Ian M. Harrower, Tomás Vinar:
New Bounds for Motif Finding in Strong Instances. CPM 2006: 94-105 - 2005
- [j5]Alexander K. Hudek, Daniel G. Brown:
Ancestral sequence alignment under optimal conditions. BMC Bioinform. 6: 273 (2005) - [j4]Brona Brejová, Daniel G. Brown, Tomás Vinar:
Vector seeds: An extension to spaced seeds. J. Comput. Syst. Sci. 70(3): 364-380 (2005) - [j3]Daniel G. Brown:
Optimizing Multiple Seeds for Protein Homology Search. IEEE ACM Trans. Comput. Biol. Bioinform. 2(1): 29-38 (2005) - [c13]Emily W. Xu, Daniel G. Brown, Paul Kearney:
The use of functional domains to improve transmembrane protein topology prediction. APBC 2005: 105-116 - [c12]Brona Brejová, Daniel G. Brown, Ian M. Harrower, Alejandro López-Ortiz, Tomás Vinar:
Sharper Upper and Lower Bounds for an Approximation Scheme for Consensus-Pattern. CPM 2005: 1-10 - [c11]Brona Brejová, Daniel G. Brown, Ming Li, Tomás Vinar:
ExonHunter: a comprehensive approach to gene finding. ISMB (Supplement of Bioinformatics) 2005: 57-65 - 2004
- [j2]Brona Brejová, Daniel G. Brown, Tomás Vinar:
Optimal Spaced Seeds for Homologous Coding Regions. J. Bioinform. Comput. Biol. 1(4): 595-610 (2004) - [j1]Daniel G. Brown, Ming Li, Bin Ma:
A Tutorial of Recent Developments in the Seeding of Local Alignment. J. Bioinform. Comput. Biol. 2(4): 819-842 (2004) - [c10]Jinbo Xu, Daniel G. Brown, Ming Li, Bin Ma:
Optimizing Multiple Spaced Seeds for Homology Search. CPM 2004: 47-58 - [c9]Daniel G. Brown:
Multiple Vector Seeds for Protein Alignment. WABI 2004: 170-181 - [c8]Daniel G. Brown, Ian M. Harrower:
A New Integer Programming Formulation for the Pure Parsimony Problem in Haplotype Analysis. WABI 2004: 254-265 - [c7]Daniel G. Brown, Alexander K. Hudek:
New Algorithms for Multiple DNA Sequence Alignment. WABI 2004: 314-325 - [c6]Brona Brejová, Daniel G. Brown, Tomás Vinar:
The Most Probable Labeling Problem in HMMs and Its Application to Bioinformatics. WABI 2004: 426-437 - 2003
- [c5]Brona Brejová, Daniel G. Brown, Tomás Vinar:
Optimal Spaced Seeds for Hidden Markov Models, with Application to Homologous Coding Regions. CPM 2003: 42-54 - [c4]Brona Brejová, Daniel G. Brown, Tomás Vinar:
Vector Seeds: An Extension to Spaced Seeds Allows Substantial Improvements in Sensitivity and Specifity. WABI 2003: 39-54 - [c3]Brona Brejová, Daniel G. Brown, Tomás Vinar:
Optimal DNA Signal Recognition Models with a Fixed Amount of Intrasignal Dependency. WABI 2003: 78-94 - 2001
- [c2]Daniel G. Brown:
A probabilistic analysis of a greedy algorithm arising from computational biology. SODA 2001: 206-207 - 2000
- [b1]Daniel G. Brown:
Algorithmic Methods in Genetic Mapping. Cornell University, USA, 2000 - [c1]Daniel G. Brown, Todd J. Vision, Steven D. Tanksley:
Selective mapping: a discrete optimization approach to selecting a population subset for use in a high-density genetic mapping project. SODA 2000: 419-428
Coauthor Index
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