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2020 – today
- 2024
[i14]Katie Christensen, Lyric Otto, Seth Bassetti, Claudia Tebaldi, Brian Hutchinson:
Diffusion-Based Joint Temperature and Precipitation Emulation of Earth System Models. CoRR abs/2404.08797 (2024)- [i13]Seth Bassetti, Brian Hutchinson, Claudia Tebaldi, Ben Kravitz:
DiffESM: Conditional Emulation of Temperature and Precipitation in Earth System Models with 3D Diffusion Models. CoRR abs/2409.11601 (2024) - 2023
- [c25]Sarah Coffland
, Katie Christensen, Filip Jagodzinski, Brian Hutchinson:
RoseNet: Predicting Energy Metrics of Double InDel Mutants Using Deep Learning. BCB 2023: 107:1-107:9 - [i12]Seth Bassetti, Brian Hutchinson, Claudia Tebaldi, Ben Kravitz:
DiffESM: Conditional Emulation of Earth System Models with Diffusion Models. CoRR abs/2304.11699 (2023) - [i11]Sarah Coffland, Katie Christensen, Filip Jagodzinski, Brian Hutchinson:
RoseNet: Predicting Energy Metrics of Double InDel Mutants Using Deep Learning. CoRR abs/2310.13806 (2023) - 2021
- [i10]Alexis Ayala, Christopher Drazic, Brian Hutchinson, Ben Kravitz, Claudia Tebaldi:
Loosely Conditioned Emulation of Global Climate Models With Generative Adversarial Networks. CoRR abs/2105.06386 (2021) - [i9]Piper Wolters, Chris Daw, Brian Hutchinson, Lauren Phillips:
Proposal-based Few-shot Sound Event Detection for Speech and Environmental Sounds with Perceivers. CoRR abs/2107.13616 (2021) - [i8]Eric Slyman, Chris Daw, Morgan Skrabut, Ana Usenko, Brian Hutchinson:
Fine-Grained Classroom Activity Detection from Audio with Neural Networks. CoRR abs/2107.14369 (2021) - 2020
- [c24]Loc Truong, Chace Jones, Brian Hutchinson, Andrew August, Brenda Praggastis, Robert Jasper, Nicole Nichols, Aaron Tuor:
Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers. CVPR Workshops 2020: 3422-3431 - [i7]Loc Truong, Chace Jones, Brian Hutchinson, Andrew August, Brenda Praggastis, Robert Jasper, Nicole Nichols, Aaron Tuor:
Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers. CoRR abs/2004.11514 (2020) - [i6]Alexandra Puchko, Robert Link, Brian Hutchinson, Ben Kravitz, Abigail Snyder:
DeepClimGAN: A High-Resolution Climate Data Generator. CoRR abs/2011.11705 (2020) - [i5]Piper Wolters, Chris Careaga, Brian Hutchinson, Lauren Phillips:
A Study of Few-Shot Audio Classification. CoRR abs/2012.01573 (2020)
2010 – 2019
- 2019
- [c23]Robin Cosbey, Allison Wusterbarth, Brian Hutchinson:
Deep Learning for Classroom Activity Detection from Audio. ICASSP 2019: 3727-3731 - [c22]Svitlana Volkova, Ellyn Ayton, Dustin Lockhart Arendt, Zhuanyi Huang, Brian Hutchinson:
Explaining Multimodal Deceptive News Prediction Models. ICWSM 2019: 659-662 - [i4]Chris Careaga, Brian Hutchinson, Nathan Oken Hodas, Lawrence Phillips:
Metric-Based Few-Shot Learning for Video Action Recognition. CoRR abs/1909.09602 (2019) - 2018
- [j6]Richard Olney, Aaron Tuor, Filip Jagodzinski, Brian Hutchinson:
A systematic exploration of ΔΔG cutoff ranges in machine learning models for protein mutation stability prediction. J. Bioinform. Comput. Biol. 16(5): 1840022:1-1840022:19 (2018) - [c21]Aaron Randall Tuor, Ryan Baerwolf, Nicolas Knowles, Brian Hutchinson, Nicole Nichols, Robert Jasper:
Recurrent Neural Network Language Models for Open Vocabulary Event-Level Cyber Anomaly Detection. AAAI Workshops 2018: 285-293 - [c20]Nicholas Majeske, Filip Jagodzinski, Brian Hutchinson, Tanzima Z. Islam:
Low Rank Smoothed Sampling Methods for Identifying Impactful Pairwise Mutations. BCB 2018: 681-686 - [c19]Gracie Ermi, Ellyn Ayton, Nolan Price, Brian Hutchinson:
Deep Learning Approaches to Chemical Property Prediction from Brewing Recipes. IJCNN 2018: 1-7 - [i3]Andy Brown, Aaron Tuor, Brian Hutchinson, Nicole Nichols:
Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection. CoRR abs/1803.04967 (2018) - 2017
- [c18]Aaron Tuor, Samuel Kaplan, Brian Hutchinson, Nicole Nichols, Sean Robinson:
Predicting User Roles from Computer Logs Using Recurrent Neural Networks. AAAI 2017: 4993-4994 - [c17]Aaron Tuor, Samuel Kaplan, Brian Hutchinson, Nicole Nichols, Sean Robinson:
Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams. AAAI Workshops 2017 - [c16]Roshanak Farhoodi, Max Shelbourne, Rebecca Hsieh, Nurit Haspel, Brian Hutchinson, Filip Jagodzinski:
Predicting the Effect of Point Mutations on Protein Structural Stability. BCB 2017: 247-252 - [c15]Caleb Nelson, Yulo Leake, Brian Hutchinson:
Low n-rank tensor log-linear models for classification. IJCNN 2017: 2738-2742 - [i2]Aaron Tuor, Samuel Kaplan, Brian Hutchinson, Nicole Nichols, Sean Robinson:
Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams. CoRR abs/1710.00811 (2017) - [i1]Aaron Tuor, Ryan Baerwolf, Nicolas Knowles, Brian Hutchinson, Nicole Nichols, Robert Jasper:
Recurrent Neural Network Language Models for Open Vocabulary Event-Level Cyber Anomaly Detection. CoRR abs/1712.00557 (2017) - 2016
- [j5]Yanzhang He, Peter Baumann, Hao Fang, Brian Hutchinson, Aaron Jaech, Mari Ostendorf, Eric Fosler-Lussier, Janet B. Pierrehumbert:
Using Pronunciation-Based Morphological Subword Units to Improve OOV Handling in Keyword Search. IEEE ACM Trans. Audio Speech Lang. Process. 24(1): 79-92 (2016) - 2015
- [j4]Brian Hutchinson, Mari Ostendorf, Maryam Fazel:
A Sparse Plus Low-Rank Exponential Language Model for Limited Resource Scenarios. IEEE ACM Trans. Audio Speech Lang. Process. 23(3): 494-504 (2015) - [c14]David Palzer, Brian Hutchinson:
The Tensor Deep Stacking Network Toolkit. IJCNN 2015: 1-5 - 2014
- [c13]Yanzhang He, Brian Hutchinson, Peter Baumann, Mari Ostendorf, Eric Fosler-Lussier, Janet B. Pierrehumbert:
Subword-based modeling for handling OOV words inkeyword spotting. ICASSP 2014: 7864-7868 - 2013
- [j3]Brian Hutchinson, Li Deng, Dong Yu:
Tensor Deep Stacking Networks. IEEE Trans. Pattern Anal. Mach. Intell. 35(8): 1944-1957 (2013) - [j2]Bin Zhang, Alex Marin, Brian Hutchinson, Mari Ostendorf:
Learning Phrase Patterns for Text Classification. IEEE Trans. Speech Audio Process. 21(6): 1180-1189 (2013) - [c12]Brian Hutchinson, Mari Ostendorf, Maryam Fazel:
Exceptions in language as learned by the multi-factor sparse plus low-rank language model. ICASSP 2013: 8580-8584 - 2012
- [c11]Brian Hutchinson, Li Deng, Dong Yu:
A deep architecture with bilinear modeling of hidden representations: Applications to phonetic recognition. ICASSP 2012: 4805-4808 - [c10]Brian Hutchinson, Mari Ostendorf, Maryam Fazel:
A Sparse Plus Low Rank Maximum Entropy Language Model. INTERSPEECH 2012: 1676-1679 - [c9]Li Deng, Brian Hutchinson, Dong Yu:
Parallel Training for Deep Stacking Networks. INTERSPEECH 2012: 2598-2601 - 2011
- [j1]Brian Hutchinson, Mari Ostendorf, Maryam Fazel:
Low Rank Language Models for Small Training Sets. IEEE Signal Process. Lett. 18(9): 489-492 (2011) - [c8]Bin Zhang, Alex Marin, Brian Hutchinson, Mari Ostendorf:
Analyzing conversations using rich phrase patterns. ASRU 2011: 443-448 - [c7]Brian Hutchinson, Jasha Droppo:
Learning non-parametric models of pronunciation. ICASSP 2011: 4904-4907 - 2010
- [c6]Brian Hutchinson, Bin Zhang, Mari Ostendorf:
Unsupervised broadcast conversation speaker role labeling. ICASSP 2010: 5322-5325 - [c5]Bin Zhang, Brian Hutchinson, Wei Wu, Mari Ostendorf:
Extracting Phrase Patterns with Minimum Redundancy for Unsupervised Speaker Role Classification. HLT-NAACL 2010: 717-720 - [c4]Meghan Oxley, Jonathan T. Morgan, Mark Zachry, Brian Hutchinson:
"What i know is...": establishing credibility on Wikipedia talk pages. Int. Sym. Wikis 2010
2000 – 2009
- 2008
- [c3]Amy Dashiell, Brian Hutchinson, Anna Margolis, Mari Ostendorf:
Non-segmental duration feature extraction for prosodic classification. INTERSPEECH 2008: 1092-1095 - [c2]Arno R. Lodder, Andrea Borri, Jacques Gouimenou, Brian Hutchinson, Vincent Tilman:
Towards Standardisation of Online Dispute Resolution Tools. ODR 2008 - 2006
- [c1]Brian Hutchinson, Jianna Zhang:
Multiclass Support Vector Machines for Articulatory Feature Classification. AAAI 2006: 1871-1872
Coauthor Index
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last updated on 2024-10-22 21:17 CEST by the dblp team
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