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ORCIDMarissa Connor
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- affiliation: Georgia Institute of Technology, Atlanta, GA, USA
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2020 – today
- 2024
[i7]Stephen Casper, Jieun Yun, Joonhyuk Baek, Yeseong Jung, Minhwan Kim, Kiwan Kwon, Saerom Park, Hayden Moore, David Shriver, Marissa Connor, Keltin Grimes, Angus Nicolson, Arush Tagade, Jessica Rumbelow, Hieu Minh Nguyen, Dylan Hadfield-Menell:
The SaTML '24 CNN Interpretability Competition: New Innovations for Concept-Level Interpretability. CoRR abs/2404.02949 (2024)- 2023
- [j1]Marissa Catherine Connor, Kion Fallah, Christopher John Rozell
:
Learning Identity-Preserving Transformations on Data Manifolds. Trans. Mach. Learn. Res. 2023 (2023) - [i6]Marissa Connor, Bruno A. Olshausen, Christopher Rozell:
Learning Internal Representations of 3D Transformations from 2D Projected Inputs. CoRR abs/2303.17776 (2023) - 2022
- [b1]Marissa Connor:
Structured Learning with Manifold Representations of Natural Data Variations. Georgia Institute of Technology, Atlanta, GA, USA, 2022 - [i5]Marissa Connor, Vincent Emanuele:
Rethinking Backdoor Data Poisoning Attacks in the Context of Semi-Supervised Learning. CoRR abs/2212.02582 (2022) - 2021
- [c4]Marissa Connor, Gregory Canal, Christopher Rozell:
Variational Autoencoder with Learned Latent Structure. AISTATS 2021: 2359-2367 - [i4]Marissa Connor, Kion Fallah, Christopher Rozell:
Learning Identity-Preserving Transformations on Data Manifolds. CoRR abs/2106.12096 (2021) - 2020
- [c3]Marissa Connor, Christopher Rozell:
Representing Closed Transformation Paths in Encoded Network Latent Space. AAAI 2020: 3666-3675 - [c2]Gregory Canal, Marissa Connor, Jihui Jin, Namrata Nadagouda, Matthew R. O'Shaughnessy, Christopher J. Rozell, Mark A. Davenport:
The Picasso Algorithm for Bayesian Localization Via Paired Comparisons in a Union of Subspaces Model. ICASSP 2020: 3462-3466 - [c1]Matthew R. O'Shaughnessy, Gregory Canal, Marissa Connor, Christopher Rozell, Mark A. Davenport:
Generative causal explanations of black-box classifiers. NeurIPS 2020 - [i3]Marissa Connor, Gregory H. Canal, Christopher J. Rozell:
Variational Autoencoder with Learned Latent Structure. CoRR abs/2006.10597 (2020) - [i2]Matthew R. O'Shaughnessy, Gregory Canal, Marissa Connor, Mark A. Davenport, Christopher Rozell:
Generative causal explanations of black-box classifiers. CoRR abs/2006.13913 (2020)
2010 – 2019
- 2019
- [i1]Marissa Connor, Christopher Rozell:
Representing Closed Transformation Paths in Encoded Network Latent Space. CoRR abs/1912.02644 (2019)
Coauthor Index
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