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2020 – today
- 2024
[i26]Ashwin Samudre, Mircea Petrache, Brian Nord, Shubhendu Trivedi:
Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks. CoRR abs/2409.11772 (2024)- 2023
- [j14]Davide Piras
, Hiranya V. Peiris, Andrew Pontzen, Luisa Lucie-Smith, Ningyuan Guo, Brian Nord:
A robust estimator of mutual information for deep learning interpretability. Mach. Learn. Sci. Technol. 4(2): 25006 (2023) - [j13]Aleksandra Ciprijanovic, Ashia Lewis, Kevin Pedro, Sandeep Madireddy, Brian Nord, Gabriel N. Perdue, Stefan M. Wild:
DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection. Mach. Learn. Sci. Technol. 4(2): 25013 (2023) - [i25]Aleksandra Ciprijanovic, Ashia Lewis, Kevin Pedro, Sandeep Madireddy, Brian Nord, Gabriel N. Perdue, Stefan M. Wild:
DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection. CoRR abs/2302.02005 (2023) - [i24]Samuel D. McDermott, Maggie Voetberg, Brian Nord:
WavPool: A New Block for Deep Neural Networks. CoRR abs/2306.08734 (2023) - [i23]Daniela Huppenkothen, Michelle Ntampaka, M. Ho, M. Fouesneau, Brian Nord, Joshua E. G. Peek, Mike Walmsley, John F. Wu, Camille Avestruz, T. Buck, M. Brescia, D. P. Finkbeiner, Andy D. Goulding, Tomasz Kacprzak, Peter Melchior, M. Pasquato, Nesar Ramachandra, Yuan-Sen Ting, G. van de Ven, S. Villar, V. A. Villar, E. Zinger:
Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers. CoRR abs/2310.12528 (2023) - [i22]Andrea Roncoli, Aleksandra Ciprijanovic, Maggie Voetberg, Francisco Villaescusa-Navarro, Brian Nord:
Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets. CoRR abs/2311.01588 (2023) - [i21]Franco Terranova, Maggie Voetberg, Brian Nord, Amanda Pagul:
Self-Driving Telescopes: Autonomous Scheduling of Astronomical Observation Campaigns with Offline Reinforcement Learning. CoRR abs/2311.18094 (2023) - 2022
- [j12]Dimitrios Tanoglidis, Aleksandra Ciprijanovic, Alex Drlica-Wagner, Brian Nord, Michael H. L. S. Wang, A. Jacob Amsellem, K. Downey, S. Jenkins, Diana Kafkes, Z. Zhang:
DeepGhostBusters: Using Mask R-CNN to detect and mask ghosting and scattered-light artifacts from optical survey images. Astron. Comput. 39: 100580 (2022) - [j11]Aleksandra Ciprijanovic, Diana Kafkes, Gregory F. Snyder, F. Javier Sánchez, Gabriel Nathan Perdue, Kevin Pedro, Brian Nord, Sandeep Madireddy, Stefan M. Wild:
DeepAdversaries: examining the robustness of deep learning models for galaxy morphology classification. Mach. Learn. Sci. Technol. 3(3): 35007 (2022) - [j10]Gourav Khullar, Brian Nord, Aleksandra Ciprijanovic, Jason Poh, Fei Xu:
DIGS: deep inference of galaxy spectra with neural posterior estimation. Mach. Learn. Sci. Technol. 3(4): 4 (2022) - [i20]Cora Dvorkin, Siddharth Mishra-Sharma, Brian Nord, V. Ashley Villar, Camille Avestruz, Keith Bechtol, Aleksandra Ciprijanovic, Andrew J. Connolly, Lehman H. Garrison, Gautham Narayan, Francisco Villaescusa-Navarro:
Machine Learning and Cosmology. CoRR abs/2203.08056 (2022) - [i19]Fengxue Zhang, Brian Nord, Yuxin Chen:
Learning Representation for Bayesian Optimization with Collision-free Regularization. CoRR abs/2203.08656 (2022) - [i18]Luisa Lucie-Smith, Hiranya V. Peiris, Andrew Pontzen, Brian Nord, Jeyan Thiyagalingam, Davide Piras:
Discovering the building blocks of dark matter halo density profiles with neural networks. CoRR abs/2203.08827 (2022) - [i17]Thomas Y. Chen, Biprateep Dey, Aishik Ghosh, Michael Kagan, Brian Nord, Nesar Ramachandra:
Interpretable Uncertainty Quantification in AI for HEP. CoRR abs/2208.03284 (2022) - [i16]Davide Piras, Hiranya V. Peiris, Andrew Pontzen, Luisa Lucie-Smith, Ningyuan Guo, Brian Nord:
A robust estimator of mutual information for deep learning interpretability. CoRR abs/2211.00024 (2022) - [i15]Aleksandra Ciprijanovic, Ashia Lewis, Kevin Pedro, Sandeep Madireddy, Brian Nord, Gabriel N. Perdue, Stefan M. Wild:
Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection. CoRR abs/2211.00677 (2022) - [i14]Egor Danilov, Aleksandra Ciprijanovic, Brian Nord:
Neural Inference of Gaussian Processes for Time Series Data of Quasars. CoRR abs/2211.10305 (2022) - 2021
- [j9]Chihway L. Chang, Alex Drlica-Wagner, S. M. Kent, Brian Nord, Donah Michelle Wang, Michael H. L. S. Wang:
A machine learning approach to the detection of ghosting and scattered light artifacts in dark energy survey images. Astron. Comput. 36: 100474 (2021) - [j8]Robert Morgan, Brian Nord, Simon Birrer, Joshua Yao-Yu Lin, Jason Poh:
deeplenstronomy: A dataset simulation package for strong gravitational lensing. J. Open Source Softw. 6(58): 2854 (2021) - [j7]Adam Amara, Lucia de la Bella, Simon Birrer, Sarah Bridle, Juan Cordero, Ginevra Favole, Ian Harrison, Ian Harry, William G. Hartley, Coleman Krawczyk, Andrew Lundgren, Brian Nord, Laura Nuttall, Richard Rollins, Philipp Sudek, Sut-Ieng Tam, Nicolas Tessore, Arthur Tolley, Keiichi Umetsu, Andrew Williamson, Laura Wolz:
SkyPy: A package for modelling the Universe. J. Open Source Softw. 6(68): 3056 (2021) - [j6]João Caldeira, Brian Nord:
Deeply uncertain: comparing methods of uncertainty quantification in deep learning algorithms. Mach. Learn. Sci. Technol. 2(1): 15002 (2021) - [j5]Faryad Sahneh, Meghan A. Balk, Marina Kisley, Chi-Kwan Chan, Mercury Fox, Brian Nord, Eric Lyons, Tyson Lee Swetnam, Daniela Huppenkothen, Will Sutherland, Ramona L. Walls, Daven P. Quinn, Tonantzin Tarin, David S. LeBauer, David Ribes, Dunbar P. Birnie III, Carol Lushbough, Eric Carr, Grey Nearing, Jeremy Fischer, Kevin Tyle, Luis Carrasco, Meagan Lang, Peter W. Rose, Richard R. Rushforth, Samapriya Roy, Thomas Matheson, Tina Lee, C. Titus Brown, Tracy K. Teal, Monica Papes, Stephen G. Kobourov, Nirav C. Merchant:
Ten simple rules to cultivate transdisciplinary collaboration in data science. PLoS Comput. Biol. 17(5) (2021) - [i13]Zhen Lin, Nicholas Huang, Camille Avestruz, W. L. Kimmy Wu, Shubhendu Trivedi, João Caldeira, Brian Nord:
DeepSZ: Identification of Sunyaev-Zel'dovich Galaxy Clusters using Deep Learning. CoRR abs/2102.13123 (2021) - [i12]Aleksandra Ciprijanovic, Diana Kafkes, K. Downey, S. Jenkins, Gabriel N. Perdue, Sandeep Madireddy, T. Johnston, Gregory F. Snyder, Brian Nord:
DeepMerge II: Building Robust Deep Learning Algorithms for Merging Galaxy Identification Across Domains. CoRR abs/2103.01373 (2021) - [i11]Miles D. Cranmer, Peter Melchior, Brian Nord:
Unsupervised Resource Allocation with Graph Neural Networks. CoRR abs/2106.09761 (2021) - [i10]Aleksandra Ciprijanovic, Diana Kafkes, Gabriel N. Perdue, Kevin Pedro, Gregory F. Snyder, F. Javier Sánchez, Sandeep Madireddy, Stefan M. Wild, Brian Nord:
Robustness of deep learning algorithms in astronomy - galaxy morphology studies. CoRR abs/2111.00961 (2021) - [i9]Aleksandra Ciprijanovic, Diana Kafkes, Gregory F. Snyder, F. Javier Sánchez, Gabriel Nathan Perdue, Kevin Pedro, Brian Nord, Sandeep Madireddy, Stefan M. Wild:
DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification. CoRR abs/2112.14299 (2021) - 2020
- [j4]Aleksandra Ciprijanovic, Gregory F. Snyder, Brian Nord, Joshua E. G. Peek:
DeepMerge: Classifying high-redshift merging galaxies with deep neural networks. Astron. Comput. 32: 100390 (2020) - [c2]Miles D. Cranmer, Peter Melchior, Brian Nord:
Unsupervised Resource Allocation with Graph Neural Networks. Preregister@NeurIPS 2020: 272-284 - [i8]João Caldeira, Brian Nord:
Deeply Uncertain: Comparing Methods of Uncertainty Quantification in Deep Learning Algorithms. CoRR abs/2004.10710 (2020) - [i7]Aleksandra Ciprijanovic, Gregory F. Snyder, Brian Nord, Joshua E. G. Peek:
DeepMerge: Classifying High-redshift Merging Galaxies with Deep Neural Networks. CoRR abs/2004.11981 (2020) - [i6]Aleksandra Ciprijanovic, Diana Kafkes, S. Jenkins, K. Downey, Gabriel N. Perdue, Sandeep Madireddy, T. Johnston, Brian Nord:
Domain adaptation techniques for improved cross-domain study of galaxy mergers. CoRR abs/2011.03591 (2020) - [i5]Luisa Lucie-Smith, Hiranya V. Peiris, Andrew Pontzen, Brian Nord, Jeyan Thiyagalingam:
Deep learning insights into cosmological structure formation. CoRR abs/2011.10577 (2020)
2010 – 2019
- 2019
- [j3]João Caldeira, W. L. K. Wu, Brian Nord, Camille Avestruz, Shubhendu Trivedi, K. T. Story:
DeepCMB: Lensing reconstruction of the cosmic microwave background with deep neural networks. Astron. Comput. 28: 100307 (2019) - [c1]M. J. Marquez, Brian Nord:
Challenges and Approaches for Mining Astronomical Data and Complex Models. BCD 2019: 54-59 - [i4]Brian Nord, Andrew J. Connolly, Jamie Kinney, Jeremy Kubica, Gautaum Narayan, Joshua E. G. Peek, Chad Schafer, Erik J. Tollerud, Camille Avestruz, Gutti Jogesh Babu, Simon Birrer, Douglas Burke, João Caldeira, Douglas A. Caldwell, Joleen K. Carlberg, Yen-Chi Chen, Chuanfei Dong, Eric D. Feigelson, V. Zach Golkhou, Vinay Kashyap, T. S. Li, Thomas Loredo, Luisa Lucie-Smith, Kaisey S. Mandel, J. R. Martínez-Galarza, Adam A. Miller, Priyamvada Natarajan, Michelle Ntampaka, Andy Ptak, David Rapetti, Lior Shamir, Aneta Siemiginowska, Brigitta M. Sipocz, Arfon M. Smith, Nhan Tran, Ricardo Vilalta, Lucianne M. Walkowicz, John ZuHone:
Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era. CoRR abs/1911.02479 (2019) - [i3]James F. Amundson, James Annis, Camille Avestruz, D. Bowring, João Caldeira, Giuseppe Cerati, Chihway L. Chang, Scott Dodelson, D. Elvira, A. Farahi, Krzysztof L. Genser, Lindsey Gray, Oliver Gutsche, Philip C. Harris, Jamie Kinney, James B. Kowalkowski, Rob Kutschke, S. Mrenna, Brian Nord, A. Para, Kevin Pedro, Gabriel N. Perdue, Alexander Scheinker, Panagiotis Spentzouris, J. St. John, Nhan Tran, Shubhendu Trivedi, Laura Trouille, W. L. K. Wu, C. R. Bom:
Response to NITRD, NCO, NSF Request for Information on "Update to the 2016 National Artificial Intelligence Research and Development Strategic Plan". CoRR abs/1911.05796 (2019) - [i2]João Caldeira, Joshua Job, Steven H. Adachi, Brian Nord, Gabriel N. Perdue:
Restricted Boltzmann Machines for galaxy morphology classification with a quantum annealer. CoRR abs/1911.06259 (2019) - 2018
- [i1]João Caldeira, W. L. K. Wu, Brian Nord, Camille Avestruz, Shubhendu Trivedi, K. T. Story:
DeepCMB: Lensing Reconstruction of the Cosmic Microwave Background with Deep Neural Networks. CoRR abs/1810.01483 (2018) - 2016
- [j2]Brian Nord, Adam Amara, Alexandre Réfrégier, La. Gamper, Lukas Gamper, B. Hambrecht, Chihway L. Chang, Jaime E. Forero-Romero, Santiago Serrano, Carla Cunha, O. Coles, Andrina Nicola, Michael T. Busha, Anne H. Bauer, Will J. Saunders, Stéphanie Jouvel, Donnacha Kirk, Risa H. Wechsler:
SPOKES: An end-to-end simulation facility for spectroscopic cosmological surveys. Astron. Comput. 15: 1-15 (2016) - [j1]Peter Melchior, Erin Sheldon, Alex Drlica-Wagner, Eli S. Rykoff, Timothy M. C. Abbott, Filipe B. Abdalla, Sahar Allam, Aurélien Benoit-Lévy, David D. Brooks, Elizabeth Buckley-Geer, Aurelio Carnero Rosell, Matias Carrasco Kind, Jorge Carretero, Martín Crocce, Chris D'Andrea, Luiz Nicolaci da Costa, Shantanu Desai, Peter Doel, August E. Evrard, David A. Finley, Brenna L. Flaugher, Joshua A. Frieman, Enrique Gaztañaga, David W. Gerdes, Daniel Gruen, Richard A. Gruendl, Klaus Honscheid, David J. James, Michael J. Jarvis, Kyler W. Kuehn, Ting S. Li, Marcio A. G. Maia, Marisa C. March, Jennifer L. Marshall, Brian Nord, Ricardo Ogando, Andreas Alejandro Plazas, Anita K. Römer, Eusebio Sánchez, Victor E. Scarpine, Ignacio Sevilla-Noarbe, Robert C. Smith, Marcelle Soares-Santos, Eric Suchyta, Mollye E. C. Swanson, Gregory G. Tarlé, Vinu Vikram, Alistair R. Walker, William C. Wester, Yuanyuan Zhang:
Crowdsourcing quality control for Dark Energy Survey images. Astron. Comput. 16: 99-108 (2016)
Coauthor Index
aka: Gabriel Nathan Perdue
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